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applications</span> </div> </a> <ul id="toc-Security_applications-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Biomedical_applications" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Biomedical_applications"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.2</span> <span>Biomedical applications</span> </div> </a> <ul id="toc-Biomedical_applications-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Software_applications" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Software_applications"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.3</span> <span>Software applications</span> </div> </a> <ul id="toc-Software_applications-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Online_media_applications" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Online_media_applications"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.4</span> <span>Online media applications</span> </div> </a> <ul id="toc-Online_media_applications-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Business_and_marketing_applications" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Business_and_marketing_applications"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.5</span> <span>Business and marketing applications</span> </div> </a> <ul id="toc-Business_and_marketing_applications-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Sentiment_analysis" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Sentiment_analysis"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.6</span> <span>Sentiment analysis</span> </div> </a> <ul id="toc-Sentiment_analysis-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Scientific_literature_mining_and_academic_applications" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Scientific_literature_mining_and_academic_applications"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.7</span> <span>Scientific literature mining and academic applications</span> </div> </a> <ul id="toc-Scientific_literature_mining_and_academic_applications-sublist" class="vector-toc-list"> <li id="toc-Methods_for_scientific_literature_mining" class="vector-toc-list-item vector-toc-level-3"> <a class="vector-toc-link" href="#Methods_for_scientific_literature_mining"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.7.1</span> <span>Methods for scientific literature mining</span> </div> </a> <ul id="toc-Methods_for_scientific_literature_mining-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Digital_humanities_and_computational_sociology" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Digital_humanities_and_computational_sociology"> <div class="vector-toc-text"> <span class="vector-toc-numb">3.8</span> <span>Digital humanities and computational sociology</span> </div> </a> <ul id="toc-Digital_humanities_and_computational_sociology-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Software" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Software"> <div class="vector-toc-text"> <span class="vector-toc-numb">4</span> <span>Software</span> </div> </a> <ul id="toc-Software-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Intellectual_property_law" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Intellectual_property_law"> <div class="vector-toc-text"> <span class="vector-toc-numb">5</span> <span>Intellectual property law</span> </div> </a> <button aria-controls="toc-Intellectual_property_law-sublist" class="cdx-button cdx-button--weight-quiet cdx-button--icon-only vector-toc-toggle"> <span class="vector-icon mw-ui-icon-wikimedia-expand"></span> <span>Toggle Intellectual property law subsection</span> </button> <ul id="toc-Intellectual_property_law-sublist" class="vector-toc-list"> <li id="toc-Situation_in_Europe" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Situation_in_Europe"> <div class="vector-toc-text"> <span class="vector-toc-numb">5.1</span> <span>Situation in Europe</span> </div> </a> <ul id="toc-Situation_in_Europe-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Situation_in_the_United_States" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Situation_in_the_United_States"> <div class="vector-toc-text"> <span class="vector-toc-numb">5.2</span> <span>Situation in the United States</span> </div> </a> <ul id="toc-Situation_in_the_United_States-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Situation_in_Australia" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Situation_in_Australia"> <div class="vector-toc-text"> <span class="vector-toc-numb">5.3</span> <span>Situation in Australia</span> </div> </a> <ul id="toc-Situation_in_Australia-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-Implications" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#Implications"> <div class="vector-toc-text"> <span class="vector-toc-numb">6</span> <span>Implications</span> </div> </a> <ul id="toc-Implications-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-See_also" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#See_also"> <div class="vector-toc-text"> <span class="vector-toc-numb">7</span> <span>See also</span> </div> </a> <ul id="toc-See_also-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-References" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#References"> <div class="vector-toc-text"> <span class="vector-toc-numb">8</span> <span>References</span> </div> </a> <button aria-controls="toc-References-sublist" class="cdx-button cdx-button--weight-quiet cdx-button--icon-only vector-toc-toggle"> <span class="vector-icon mw-ui-icon-wikimedia-expand"></span> <span>Toggle References subsection</span> </button> <ul id="toc-References-sublist" class="vector-toc-list"> <li id="toc-Citations" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Citations"> <div class="vector-toc-text"> <span class="vector-toc-numb">8.1</span> <span>Citations</span> </div> </a> <ul id="toc-Citations-sublist" class="vector-toc-list"> </ul> </li> <li id="toc-Sources" class="vector-toc-list-item vector-toc-level-2"> <a class="vector-toc-link" href="#Sources"> <div class="vector-toc-text"> <span class="vector-toc-numb">8.2</span> <span>Sources</span> </div> </a> <ul id="toc-Sources-sublist" class="vector-toc-list"> </ul> </li> </ul> </li> <li id="toc-External_links" class="vector-toc-list-item vector-toc-level-1 vector-toc-list-item-expanded"> <a class="vector-toc-link" href="#External_links"> <div class="vector-toc-text"> <span class="vector-toc-numb">9</span> <span>External links</span> </div> </a> <ul id="toc-External_links-sublist" class="vector-toc-list"> </ul> </li> </ul> </div> </div> </nav> </div> </div> <div class="mw-content-container"> <main id="content" class="mw-body"> <header class="mw-body-header vector-page-titlebar"> <nav aria-label="Contents" class="vector-toc-landmark"> <div id="vector-page-titlebar-toc" class="vector-dropdown vector-page-titlebar-toc vector-button-flush-left" > <input type="checkbox" id="vector-page-titlebar-toc-checkbox" role="button" aria-haspopup="true" data-event-name="ui.dropdown-vector-page-titlebar-toc" class="vector-dropdown-checkbox " aria-label="Toggle the table of contents" > <label id="vector-page-titlebar-toc-label" for="vector-page-titlebar-toc-checkbox" class="vector-dropdown-label cdx-button cdx-button--fake-button cdx-button--fake-button--enabled cdx-button--weight-quiet cdx-button--icon-only " aria-hidden="true" ><span class="vector-icon mw-ui-icon-listBullet mw-ui-icon-wikimedia-listBullet"></span> <span class="vector-dropdown-label-text">Toggle the table of contents</span> </label> <div class="vector-dropdown-content"> <div id="vector-page-titlebar-toc-unpinned-container" class="vector-unpinned-container"> </div> </div> </div> </nav> <h1 id="firstHeading" class="firstHeading mw-first-heading"><span class="mw-page-title-main">Text mining</span></h1> <div id="p-lang-btn" class="vector-dropdown mw-portlet mw-portlet-lang" > <input type="checkbox" id="p-lang-btn-checkbox" role="button" aria-haspopup="true" data-event-name="ui.dropdown-p-lang-btn" class="vector-dropdown-checkbox mw-interlanguage-selector" aria-label="Go to an article in another language. Available in 33 languages" > <label id="p-lang-btn-label" for="p-lang-btn-checkbox" class="vector-dropdown-label cdx-button cdx-button--fake-button cdx-button--fake-button--enabled cdx-button--weight-quiet cdx-button--action-progressive mw-portlet-lang-heading-33" aria-hidden="true" ><span class="vector-icon mw-ui-icon-language-progressive mw-ui-icon-wikimedia-language-progressive"></span> <span class="vector-dropdown-label-text">33 languages</span> </label> <div class="vector-dropdown-content"> <div class="vector-menu-content"> <ul class="vector-menu-content-list"> <li class="interlanguage-link interwiki-ar mw-list-item"><a href="https://ar.wikipedia.org/wiki/%D8%AA%D9%86%D9%82%D9%8A%D8%A8_%D9%81%D9%8A_%D8%A7%D9%84%D9%86%D8%B5%D9%88%D8%B5" title="تنقيب في النصوص – Arabic" lang="ar" hreflang="ar" data-title="تنقيب في النصوص" data-language-autonym="العربية" data-language-local-name="Arabic" class="interlanguage-link-target"><span>العربية</span></a></li><li class="interlanguage-link interwiki-bg mw-list-item"><a href="https://bg.wikipedia.org/wiki/%D0%98%D0%B7%D0%B2%D0%BB%D0%B8%D1%87%D0%B0%D0%BD%D0%B5_%D0%BD%D0%B0_%D0%B7%D0%BD%D0%B0%D0%BD%D0%B8%D1%8F_%D0%BE%D1%82_%D1%82%D0%B5%D0%BA%D1%81%D1%82" title="Извличане на знания от текст – Bulgarian" lang="bg" hreflang="bg" data-title="Извличане на знания от текст" data-language-autonym="Български" data-language-local-name="Bulgarian" class="interlanguage-link-target"><span>Български</span></a></li><li class="interlanguage-link interwiki-bs mw-list-item"><a href="https://bs.wikipedia.org/wiki/Rudarenje_tekstualnih_podataka" title="Rudarenje tekstualnih podataka – Bosnian" lang="bs" hreflang="bs" data-title="Rudarenje tekstualnih podataka" data-language-autonym="Bosanski" data-language-local-name="Bosnian" class="interlanguage-link-target"><span>Bosanski</span></a></li><li class="interlanguage-link interwiki-ca mw-list-item"><a href="https://ca.wikipedia.org/wiki/Mineria_de_textos" title="Mineria de textos – Catalan" lang="ca" hreflang="ca" data-title="Mineria de textos" data-language-autonym="Català" data-language-local-name="Catalan" class="interlanguage-link-target"><span>Català</span></a></li><li class="interlanguage-link interwiki-cs mw-list-item"><a href="https://cs.wikipedia.org/wiki/Dolov%C3%A1n%C3%AD_z_textu" title="Dolování z textu – Czech" lang="cs" hreflang="cs" data-title="Dolování z textu" data-language-autonym="Čeština" data-language-local-name="Czech" class="interlanguage-link-target"><span>Čeština</span></a></li><li class="interlanguage-link interwiki-de mw-list-item"><a href="https://de.wikipedia.org/wiki/Text_Mining" title="Text Mining – German" lang="de" hreflang="de" data-title="Text Mining" data-language-autonym="Deutsch" data-language-local-name="German" class="interlanguage-link-target"><span>Deutsch</span></a></li><li class="interlanguage-link interwiki-et mw-list-item"><a href="https://et.wikipedia.org/wiki/Tekstikaeve" title="Tekstikaeve – Estonian" lang="et" hreflang="et" data-title="Tekstikaeve" data-language-autonym="Eesti" data-language-local-name="Estonian" class="interlanguage-link-target"><span>Eesti</span></a></li><li class="interlanguage-link interwiki-el mw-list-item"><a href="https://el.wikipedia.org/wiki/%CE%95%CE%BE%CF%8C%CF%81%CF%85%CE%BE%CE%B7_%CE%BA%CE%B5%CE%B9%CE%BC%CE%AD%CE%BD%CE%BF%CF%85" title="Εξόρυξη κειμένου – Greek" lang="el" hreflang="el" data-title="Εξόρυξη κειμένου" data-language-autonym="Ελληνικά" data-language-local-name="Greek" class="interlanguage-link-target"><span>Ελληνικά</span></a></li><li class="interlanguage-link interwiki-es mw-list-item"><a href="https://es.wikipedia.org/wiki/Miner%C3%ADa_de_textos" title="Minería de textos – Spanish" lang="es" hreflang="es" data-title="Minería de textos" data-language-autonym="Español" data-language-local-name="Spanish" class="interlanguage-link-target"><span>Español</span></a></li><li class="interlanguage-link interwiki-eu mw-list-item"><a href="https://eu.wikipedia.org/wiki/Testu-meatzaritza" title="Testu-meatzaritza – Basque" lang="eu" hreflang="eu" data-title="Testu-meatzaritza" data-language-autonym="Euskara" data-language-local-name="Basque" class="interlanguage-link-target"><span>Euskara</span></a></li><li class="interlanguage-link interwiki-fa mw-list-item"><a href="https://fa.wikipedia.org/wiki/%D9%85%D8%AA%D9%86%E2%80%8C%DA%A9%D8%A7%D9%88%DB%8C" title="متن‌کاوی – Persian" lang="fa" hreflang="fa" data-title="متن‌کاوی" data-language-autonym="فارسی" data-language-local-name="Persian" class="interlanguage-link-target"><span>فارسی</span></a></li><li class="interlanguage-link interwiki-fr mw-list-item"><a href="https://fr.wikipedia.org/wiki/Fouille_de_textes" title="Fouille de textes – French" lang="fr" hreflang="fr" data-title="Fouille de textes" data-language-autonym="Français" data-language-local-name="French" class="interlanguage-link-target"><span>Français</span></a></li><li class="interlanguage-link interwiki-ko mw-list-item"><a href="https://ko.wikipedia.org/wiki/%ED%85%8D%EC%8A%A4%ED%8A%B8_%EB%A7%88%EC%9D%B4%EB%8B%9D" title="텍스트 마이닝 – Korean" lang="ko" hreflang="ko" data-title="텍스트 마이닝" data-language-autonym="한국어" data-language-local-name="Korean" class="interlanguage-link-target"><span>한국어</span></a></li><li class="interlanguage-link interwiki-id mw-list-item"><a href="https://id.wikipedia.org/wiki/Penambangan_teks" title="Penambangan teks – Indonesian" lang="id" hreflang="id" data-title="Penambangan teks" data-language-autonym="Bahasa Indonesia" data-language-local-name="Indonesian" class="interlanguage-link-target"><span>Bahasa Indonesia</span></a></li><li class="interlanguage-link interwiki-it mw-list-item"><a href="https://it.wikipedia.org/wiki/Text_mining" title="Text mining – Italian" lang="it" hreflang="it" data-title="Text mining" data-language-autonym="Italiano" data-language-local-name="Italian" class="interlanguage-link-target"><span>Italiano</span></a></li><li class="interlanguage-link interwiki-he mw-list-item"><a href="https://he.wikipedia.org/wiki/%D7%9B%D7%A8%D7%99%D7%99%D7%AA_%D7%98%D7%A7%D7%A1%D7%98" title="כריית טקסט – Hebrew" lang="he" hreflang="he" data-title="כריית טקסט" data-language-autonym="עברית" data-language-local-name="Hebrew" class="interlanguage-link-target"><span>עברית</span></a></li><li class="interlanguage-link interwiki-kn mw-list-item"><a href="https://kn.wikipedia.org/wiki/%E0%B2%AA%E0%B2%A0%E0%B3%8D%E0%B2%AF_%E0%B2%97%E0%B2%A3%E0%B2%BF%E0%B2%97%E0%B2%BE%E0%B2%B0%E0%B2%BF%E0%B2%95%E0%B3%86" title="ಪಠ್ಯ ಗಣಿಗಾರಿಕೆ – Kannada" lang="kn" hreflang="kn" data-title="ಪಠ್ಯ ಗಣಿಗಾರಿಕೆ" data-language-autonym="ಕನ್ನಡ" data-language-local-name="Kannada" class="interlanguage-link-target"><span>ಕನ್ನಡ</span></a></li><li class="interlanguage-link interwiki-hu mw-list-item"><a href="https://hu.wikipedia.org/wiki/Sz%C3%B6vegb%C3%A1ny%C3%A1szat" title="Szövegbányászat – Hungarian" lang="hu" hreflang="hu" data-title="Szövegbányászat" data-language-autonym="Magyar" data-language-local-name="Hungarian" class="interlanguage-link-target"><span>Magyar</span></a></li><li class="interlanguage-link interwiki-nl mw-list-item"><a href="https://nl.wikipedia.org/wiki/Textmining" title="Textmining – Dutch" lang="nl" hreflang="nl" data-title="Textmining" data-language-autonym="Nederlands" data-language-local-name="Dutch" class="interlanguage-link-target"><span>Nederlands</span></a></li><li class="interlanguage-link interwiki-ja mw-list-item"><a href="https://ja.wikipedia.org/wiki/%E3%83%86%E3%82%AD%E3%82%B9%E3%83%88%E3%83%9E%E3%82%A4%E3%83%8B%E3%83%B3%E3%82%B0" title="テキストマイニング – Japanese" lang="ja" hreflang="ja" data-title="テキストマイニング" data-language-autonym="日本語" data-language-local-name="Japanese" class="interlanguage-link-target"><span>日本語</span></a></li><li class="interlanguage-link interwiki-uz mw-list-item"><a href="https://uz.wikipedia.org/wiki/Intellektual_matn_tahlili" title="Intellektual matn tahlili – Uzbek" lang="uz" hreflang="uz" data-title="Intellektual matn tahlili" data-language-autonym="Oʻzbekcha / ўзбекча" data-language-local-name="Uzbek" class="interlanguage-link-target"><span>Oʻzbekcha / ўзбекча</span></a></li><li class="interlanguage-link interwiki-pl mw-list-item"><a href="https://pl.wikipedia.org/wiki/Text_mining" title="Text mining – Polish" lang="pl" hreflang="pl" data-title="Text mining" data-language-autonym="Polski" data-language-local-name="Polish" class="interlanguage-link-target"><span>Polski</span></a></li><li class="interlanguage-link interwiki-pt mw-list-item"><a href="https://pt.wikipedia.org/wiki/Minera%C3%A7%C3%A3o_de_texto" title="Mineração de texto – Portuguese" lang="pt" hreflang="pt" data-title="Mineração de texto" data-language-autonym="Português" data-language-local-name="Portuguese" class="interlanguage-link-target"><span>Português</span></a></li><li class="interlanguage-link interwiki-ru mw-list-item"><a href="https://ru.wikipedia.org/wiki/%D0%98%D0%BD%D1%82%D0%B5%D0%BB%D0%BB%D0%B5%D0%BA%D1%82%D1%83%D0%B0%D0%BB%D1%8C%D0%BD%D1%8B%D0%B9_%D0%B0%D0%BD%D0%B0%D0%BB%D0%B8%D0%B7_%D1%82%D0%B5%D0%BA%D1%81%D1%82%D0%B0" title="Интеллектуальный анализ текста – Russian" lang="ru" hreflang="ru" data-title="Интеллектуальный анализ текста" data-language-autonym="Русский" data-language-local-name="Russian" class="interlanguage-link-target"><span>Русский</span></a></li><li class="interlanguage-link interwiki-sl mw-list-item"><a href="https://sl.wikipedia.org/wiki/Rudarjenje_besedil" title="Rudarjenje besedil – Slovenian" lang="sl" hreflang="sl" data-title="Rudarjenje besedil" data-language-autonym="Slovenščina" data-language-local-name="Slovenian" class="interlanguage-link-target"><span>Slovenščina</span></a></li><li class="interlanguage-link interwiki-fi mw-list-item"><a href="https://fi.wikipedia.org/wiki/Tekstinlouhinta" title="Tekstinlouhinta – Finnish" lang="fi" hreflang="fi" data-title="Tekstinlouhinta" data-language-autonym="Suomi" data-language-local-name="Finnish" class="interlanguage-link-target"><span>Suomi</span></a></li><li class="interlanguage-link interwiki-sv mw-list-item"><a href="https://sv.wikipedia.org/wiki/Text_mining" title="Text mining – Swedish" lang="sv" hreflang="sv" data-title="Text mining" data-language-autonym="Svenska" data-language-local-name="Swedish" class="interlanguage-link-target"><span>Svenska</span></a></li><li class="interlanguage-link interwiki-th mw-list-item"><a href="https://th.wikipedia.org/wiki/%E0%B8%81%E0%B8%B2%E0%B8%A3%E0%B8%97%E0%B8%B3%E0%B9%80%E0%B8%AB%E0%B8%A1%E0%B8%B7%E0%B8%AD%E0%B8%87%E0%B8%82%E0%B9%89%E0%B8%AD%E0%B8%84%E0%B8%A7%E0%B8%B2%E0%B8%A1" title="การทำเหมืองข้อความ – Thai" lang="th" hreflang="th" data-title="การทำเหมืองข้อความ" data-language-autonym="ไทย" data-language-local-name="Thai" class="interlanguage-link-target"><span>ไทย</span></a></li><li class="interlanguage-link interwiki-tr mw-list-item"><a href="https://tr.wikipedia.org/wiki/Metin_madencili%C4%9Fi" title="Metin madenciliği – Turkish" lang="tr" hreflang="tr" data-title="Metin madenciliği" data-language-autonym="Türkçe" data-language-local-name="Turkish" class="interlanguage-link-target"><span>Türkçe</span></a></li><li class="interlanguage-link interwiki-uk mw-list-item"><a href="https://uk.wikipedia.org/wiki/%D0%86%D0%BD%D1%82%D0%B5%D0%BB%D0%B5%D0%BA%D1%82%D1%83%D0%B0%D0%BB%D1%8C%D0%BD%D0%B8%D0%B9_%D0%B0%D0%BD%D0%B0%D0%BB%D1%96%D0%B7_%D1%82%D0%B5%D0%BA%D1%81%D1%82%D1%83" title="Інтелектуальний аналіз тексту – Ukrainian" lang="uk" hreflang="uk" data-title="Інтелектуальний аналіз тексту" data-language-autonym="Українська" data-language-local-name="Ukrainian" class="interlanguage-link-target"><span>Українська</span></a></li><li class="interlanguage-link interwiki-vi mw-list-item"><a href="https://vi.wikipedia.org/wiki/Khai_th%C3%A1c_v%C4%83n_b%E1%BA%A3n" title="Khai thác văn bản – Vietnamese" lang="vi" hreflang="vi" data-title="Khai thác văn bản" data-language-autonym="Tiếng Việt" data-language-local-name="Vietnamese" class="interlanguage-link-target"><span>Tiếng Việt</span></a></li><li class="interlanguage-link interwiki-zh-yue mw-list-item"><a href="https://zh-yue.wikipedia.org/wiki/%E6%96%87%E6%9C%AC%E6%8E%A2%E5%8B%98" title="文本探勘 – Cantonese" lang="yue" hreflang="yue" data-title="文本探勘" data-language-autonym="粵語" data-language-local-name="Cantonese" class="interlanguage-link-target"><span>粵語</span></a></li><li class="interlanguage-link interwiki-zh mw-list-item"><a href="https://zh.wikipedia.org/wiki/%E6%96%87%E6%9C%AC%E6%8C%96%E6%8E%98" title="文本挖掘 – Chinese" lang="zh" hreflang="zh" data-title="文本挖掘" data-language-autonym="中文" data-language-local-name="Chinese" class="interlanguage-link-target"><span>中文</span></a></li> </ul> <div class="after-portlet after-portlet-lang"><span class="wb-langlinks-edit wb-langlinks-link"><a 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dir="ltr"><div class="shortdescription nomobile noexcerpt noprint searchaux" style="display:none">Process of analysing text to extract information from it</div> <p><b>Text mining</b>, <b>text data mining</b> (<b>TDM</b>) or <b>text analytics</b> is the process of deriving high-quality <a href="/wiki/Information" title="Information">information</a> from <a href="/wiki/Plain_text" title="Plain text">text</a>. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources."<sup id="cite_ref-1" class="reference"><a href="#cite_note-1"><span class="cite-bracket">[</span>1<span class="cite-bracket">]</span></a></sup> Written resources may include <a href="/wiki/Website" title="Website">websites</a>, <a href="/wiki/Book" title="Book">books</a>, <a href="/wiki/Email" title="Email">emails</a>, <a href="/wiki/Review" title="Review">reviews</a>, and articles. High-quality information is typically obtained by devising patterns and trends by means such as <a href="/wiki/Pattern_recognition" title="Pattern recognition">statistical pattern learning</a>. According to Hotho et al. (2005), there are three perspectives of text mining: <a href="/wiki/Information_extraction" title="Information extraction">information extraction</a>, <a href="/wiki/Data_mining" title="Data mining">data mining</a>, and <a href="/wiki/Knowledge_discovery_in_databases" class="mw-redirect" title="Knowledge discovery in databases">knowledge discovery in databases</a> (KDD).<sup id="cite_ref-2" class="reference"><a href="#cite_note-2"><span class="cite-bracket">[</span>2<span class="cite-bracket">]</span></a></sup> Text mining usually involves the process of structuring the input text (usually <a href="/wiki/Parsing" title="Parsing">parsing</a>, along with the addition of some derived linguistic features and the removal of others, and subsequent insertion into a <a href="/wiki/Database" title="Database">database</a>), deriving patterns within the <a href="/wiki/Structured_data" class="mw-redirect" title="Structured data">structured data</a>, and finally evaluation and interpretation of the output. 'High quality' in text mining usually refers to some combination of <a href="/wiki/Relevance_(information_retrieval)" title="Relevance (information retrieval)">relevance</a>, <a href="/wiki/Novelty_(patent)" title="Novelty (patent)">novelty</a>, and interest. Typical text mining tasks include <a href="/wiki/Text_categorization" class="mw-redirect" title="Text categorization">text categorization</a>, <a href="/wiki/Text_clustering" class="mw-redirect" title="Text clustering">text clustering</a>, concept/entity extraction, production of granular taxonomies, <a href="/wiki/Sentiment_analysis" title="Sentiment analysis">sentiment analysis</a>, <a href="/wiki/Document_summarization" class="mw-redirect" title="Document summarization">document summarization</a>, and <a href="/wiki/Entity%E2%80%93relationship_model" title="Entity–relationship model">entity relation modeling</a> (<i>i.e.</i>, learning relations between <a href="/wiki/Named_entity_recognition" class="mw-redirect" title="Named entity recognition">named entities</a>). </p><p>Text analysis involves <a href="/wiki/Information_retrieval" title="Information retrieval">information retrieval</a>, <a href="/wiki/Lexical_analysis" title="Lexical analysis">lexical analysis</a> to study word frequency distributions, <a href="/wiki/Pattern_recognition" title="Pattern recognition">pattern recognition</a>, <a href="/wiki/Tag_(metadata)" title="Tag (metadata)">tagging</a>/<a href="/wiki/Annotation" title="Annotation">annotation</a>, <a href="/wiki/Information_extraction" title="Information extraction">information extraction</a>, <a href="/wiki/Data_mining" title="Data mining">data mining</a> techniques including link and association analysis, <a href="/wiki/Information_visualization" class="mw-redirect" title="Information visualization">visualization</a>, and <a href="/wiki/Predictive_analytics" title="Predictive analytics">predictive analytics</a>. The overarching goal is, essentially, to turn text into data for analysis, via the application of <a href="/wiki/Natural_language_processing" title="Natural language processing">natural language processing</a> (NLP), different types of <a href="/wiki/Algorithm" title="Algorithm">algorithms</a> and analytical methods. An important phase of this process is the interpretation of the gathered information. </p><p>A typical application is to scan a set of documents written in a <a href="/wiki/Natural_language" title="Natural language">natural language</a> and either model the <a href="/wiki/Document" title="Document">document</a> set for <a href="/wiki/Predictive_classification" class="mw-redirect" title="Predictive classification">predictive classification</a> purposes or populate a database or search index with the information extracted. The <a href="/wiki/Document" title="Document">document</a> is the basic element when starting with text mining. Here, we define a document as a unit of textual data, which normally exists in many types of collections.<sup id="cite_ref-3" class="reference"><a href="#cite_note-3"><span class="cite-bracket">[</span>3<span class="cite-bracket">]</span></a></sup> </p> <meta property="mw:PageProp/toc" /> <div class="mw-heading mw-heading2"><h2 id="Text_analytics">Text analytics</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=1" title="Edit section: Text analytics"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1236090951">.mw-parser-output .hatnote{font-style:italic}.mw-parser-output div.hatnote{padding-left:1.6em;margin-bottom:0.5em}.mw-parser-output .hatnote i{font-style:normal}.mw-parser-output .hatnote+link+.hatnote{margin-top:-0.5em}@media print{body.ns-0 .mw-parser-output .hatnote{display:none!important}}</style><div role="note" class="hatnote navigation-not-searchable">See also: <a href="/wiki/List_of_text_mining_methods" title="List of text mining methods">List of text mining methods</a></div> <p><b>Text analytics</b> describes a set of <a href="/wiki/Linguistics" title="Linguistics">linguistic</a>, <a href="/wiki/Statistical" class="mw-redirect" title="Statistical">statistical</a>, and <a href="/wiki/Machine_learning" title="Machine learning">machine learning</a> techniques that model and structure the information content of textual sources for <a href="/wiki/Business_intelligence" title="Business intelligence">business intelligence</a>, <a href="/wiki/Exploratory_data_analysis" title="Exploratory data analysis">exploratory data analysis</a>, <a href="/wiki/Research" title="Research">research</a>, or investigation.<sup id="cite_ref-4" class="reference"><a href="#cite_note-4"><span class="cite-bracket">[</span>4<span class="cite-bracket">]</span></a></sup> The term is roughly synonymous with text mining; indeed, <a href="/w/index.php?title=Ronen_Feldman&action=edit&redlink=1" class="new" title="Ronen Feldman (page does not exist)">Ronen Feldman</a> modified a 2000 description of "text mining"<sup id="cite_ref-5" class="reference"><a href="#cite_note-5"><span class="cite-bracket">[</span>5<span class="cite-bracket">]</span></a></sup> in 2004 to describe "text analytics".<sup id="cite_ref-6" class="reference"><a href="#cite_note-6"><span class="cite-bracket">[</span>6<span class="cite-bracket">]</span></a></sup> The latter term is now used more frequently in business settings while "text mining" is used in some of the earliest application areas, dating to the 1980s,<sup id="cite_ref-7" class="reference"><a href="#cite_note-7"><span class="cite-bracket">[</span>7<span class="cite-bracket">]</span></a></sup> notably life-sciences research and government intelligence. </p><p>The term text analytics also describes that application of text analytics to respond to business problems, whether independently or in conjunction with query and analysis of fielded, numerical data. It is a truism that 80% of business-relevant information originates in <a href="/wiki/Unstructured_data" title="Unstructured data">unstructured</a> form, primarily text.<sup id="cite_ref-breakthroughanalysis1_8-0" class="reference"><a href="#cite_note-breakthroughanalysis1-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> These techniques and processes discover and present knowledge – facts, <a href="/wiki/Business_rule" title="Business rule">business rules</a>, and relationships – that is otherwise locked in textual form, impenetrable to automated processing. </p> <div class="mw-heading mw-heading2"><h2 id="Text_analysis_processes">Text analysis processes</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=2" title="Edit section: Text analysis processes"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Subtasks—components of a larger text-analytics effort—typically include: </p> <ul><li><a href="/wiki/Dimensionality_reduction" title="Dimensionality reduction">Dimensionality reduction</a> is important technique for pre-processing data. It is used to identify the root word for actual words and reduce the size of the text data.<sup class="noprint Inline-Template Template-Fact" style="white-space:nowrap;">[<i><a href="/wiki/Wikipedia:Citation_needed" title="Wikipedia:Citation needed"><span title="This claim needs references to reliable sources. (October 2022)">citation needed</span></a></i>]</sup></li> <li><a href="/wiki/Information_retrieval" title="Information retrieval">Information retrieval</a> or identification of a <a href="/wiki/Text_corpus" title="Text corpus">corpus</a> is a preparatory step: collecting or identifying a set of textual materials, on the Web or held in a <a href="/wiki/File_system" title="File system">file system</a>, <a href="/wiki/Database" title="Database">database</a>, or content <a href="/wiki/Corpus_manager" title="Corpus manager">corpus manager</a>, for analysis.</li> <li>Although some text analytics systems apply exclusively advanced statistical methods, many others apply more extensive <a href="/wiki/Natural_language_processing" title="Natural language processing">natural language processing</a>, such as <a href="/wiki/Part_of_speech_tagging" class="mw-redirect" title="Part of speech tagging">part of speech tagging</a>, syntactic <a href="/wiki/Parsing" title="Parsing">parsing</a>, and other types of linguistic analysis.<sup id="cite_ref-9" class="reference"><a href="#cite_note-9"><span class="cite-bracket">[</span>9<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Named_entity_recognition" class="mw-redirect" title="Named entity recognition">Named entity recognition</a> is the use of gazetteers or statistical techniques to identify named text features: people, organizations, place names, stock ticker symbols, certain abbreviations, and so on.</li> <li>Disambiguation—the use of <a href="/wiki/Context_(language_use)" class="mw-redirect" title="Context (language use)">contextual</a> clues—may be required to decide where, for instance, "Ford" can refer to a former U.S. president, a vehicle manufacturer, a movie star, a river crossing, or some other entity.<sup id="cite_ref-10" class="reference"><a href="#cite_note-10"><span class="cite-bracket">[</span>10<span class="cite-bracket">]</span></a></sup></li> <li>Recognition of pattern-identified entities: Features such as telephone numbers, e-mail addresses, quantities (with units) can be discerned via regular expression or other <a href="/wiki/Pattern_matching" title="Pattern matching">pattern matches</a>.</li> <li><a href="/wiki/Document_clustering" title="Document clustering">Document clustering</a>: identification of sets of similar text documents.<sup id="cite_ref-11" class="reference"><a href="#cite_note-11"><span class="cite-bracket">[</span>11<span class="cite-bracket">]</span></a></sup></li> <li><a href="/wiki/Coreference" title="Coreference">Coreference</a> resolution: identification of <a href="/wiki/Noun_phrase" title="Noun phrase">noun phrases</a> and other terms that refer to the same object.</li> <li>Extraction of relationships, facts and events: identification of associations among entities and other information in texts.</li> <li><a href="/wiki/Sentiment_analysis" title="Sentiment analysis">Sentiment analysis</a>: discerning of subjective material and extracting information about attitudes: sentiment, opinion, mood, and emotion. This is done at the entity, concept, or topic level and aims to distinguish opinion holders and objects.<sup id="cite_ref-12" class="reference"><a href="#cite_note-12"><span class="cite-bracket">[</span>12<span class="cite-bracket">]</span></a></sup></li> <li>Quantitative text analysis: a set of techniques stemming from the social sciences where either a human judge or a computer extracts semantic or grammatical relationships between words in order to find out the meaning or stylistic patterns of, usually, a casual personal text for the purpose of <a href="/wiki/Psychological_profiling" class="mw-redirect" title="Psychological profiling">psychological profiling</a> etc.<sup id="cite_ref-13" class="reference"><a href="#cite_note-13"><span class="cite-bracket">[</span>13<span class="cite-bracket">]</span></a></sup></li> <li>Pre-processing usually involves tasks such as tokenization, filtering and stemming.</li></ul> <div class="mw-heading mw-heading2"><h2 id="Applications">Applications</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=3" title="Edit section: Applications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Text mining technology is now broadly applied to a wide variety of government, research, and business needs. All these groups may use text mining for records management and searching documents relevant to their daily activities. Legal professionals may use text mining for <a href="/wiki/E-discovery" class="mw-redirect" title="E-discovery">e-discovery</a>, for example. Governments and military groups use text mining for <a href="/wiki/National_security" title="National security">national security</a> and intelligence purposes. Scientific researchers incorporate text mining approaches into efforts to organize large sets of text data (i.e., addressing the problem of <a href="/wiki/Unstructured_data" title="Unstructured data">unstructured data</a>), to determine ideas communicated through text (e.g., <a href="/wiki/Sentiment_analysis" title="Sentiment analysis">sentiment analysis</a> in <a href="/wiki/Social_media" title="Social media">social media</a><sup id="cite_ref-14" class="reference"><a href="#cite_note-14"><span class="cite-bracket">[</span>14<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-15" class="reference"><a href="#cite_note-15"><span class="cite-bracket">[</span>15<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-16" class="reference"><a href="#cite_note-16"><span class="cite-bracket">[</span>16<span class="cite-bracket">]</span></a></sup>) and to support <a href="/wiki/Scientific_discovery" class="mw-redirect" title="Scientific discovery">scientific discovery</a> in fields such as the <a href="/wiki/Life_sciences" class="mw-redirect" title="Life sciences">life sciences</a> and <a href="/wiki/Bioinformatics" title="Bioinformatics">bioinformatics</a>. In business, applications are used to support <a href="/wiki/Competitive_intelligence" title="Competitive intelligence">competitive intelligence</a> and automated <a href="/wiki/Ad_serving" class="mw-redirect" title="Ad serving">ad placement</a>, among numerous other activities. </p> <div class="mw-heading mw-heading3"><h3 id="Security_applications">Security applications</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=4" title="Edit section: Security applications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Many text mining software packages are marketed for <a href="/wiki/Security_appliance" title="Security appliance">security applications</a>, especially monitoring and analysis of online plain text sources such as <a href="/wiki/Internet_news" class="mw-redirect" title="Internet news">Internet news</a>, <a href="/wiki/Blog" title="Blog">blogs</a>, etc. for <a href="/wiki/National_security" title="National security">national security</a> purposes.<sup id="cite_ref-17" class="reference"><a href="#cite_note-17"><span class="cite-bracket">[</span>17<span class="cite-bracket">]</span></a></sup> It is also involved in the study of text <a href="/wiki/Encryption" title="Encryption">encryption</a>/<a href="/wiki/Decryption" class="mw-redirect" title="Decryption">decryption</a>. </p> <div class="mw-heading mw-heading3"><h3 id="Biomedical_applications">Biomedical applications</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=5" title="Edit section: Biomedical applications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1236090951"><div role="note" class="hatnote navigation-not-searchable">Main article: <a href="/wiki/Biomedical_text_mining" title="Biomedical text mining">Biomedical text mining</a></div> <figure class="mw-default-size" typeof="mw:File/Thumb"><a href="/wiki/File:Text_mining_protocol.png" class="mw-file-description"><img alt="A flowchart of a text mining protocol." src="//upload.wikimedia.org/wikipedia/commons/thumb/2/21/Text_mining_protocol.png/220px-Text_mining_protocol.png" decoding="async" width="220" height="565" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/2/21/Text_mining_protocol.png 1.5x" data-file-width="237" data-file-height="609" /></a><figcaption>An example of a text mining protocol used in a study of protein-protein complexes, or <a href="/wiki/Protein_docking" class="mw-redirect" title="Protein docking">protein docking</a>.<sup id="cite_ref-18" class="reference"><a href="#cite_note-18"><span class="cite-bracket">[</span>18<span class="cite-bracket">]</span></a></sup></figcaption></figure> <p>A range of text mining applications in the biomedical literature has been described,<sup id="cite_ref-19" class="reference"><a href="#cite_note-19"><span class="cite-bracket">[</span>19<span class="cite-bracket">]</span></a></sup> including computational approaches to assist with studies in <a href="/wiki/Protein_docking" class="mw-redirect" title="Protein docking">protein docking</a>,<sup id="cite_ref-20" class="reference"><a href="#cite_note-20"><span class="cite-bracket">[</span>20<span class="cite-bracket">]</span></a></sup> <a href="/wiki/Protein_interactions" class="mw-redirect" title="Protein interactions">protein interactions</a>,<sup id="cite_ref-21" class="reference"><a href="#cite_note-21"><span class="cite-bracket">[</span>21<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-22" class="reference"><a href="#cite_note-22"><span class="cite-bracket">[</span>22<span class="cite-bracket">]</span></a></sup> and protein-disease associations.<sup id="cite_ref-23" class="reference"><a href="#cite_note-23"><span class="cite-bracket">[</span>23<span class="cite-bracket">]</span></a></sup> In addition, with large patient textual datasets in the clinical field, datasets of demographic information in population studies and adverse event reports, text mining can facilitate clinical studies and precision medicine. Text mining algorithms can facilitate the stratification and indexing of specific clinical events in large patient textual datasets of symptoms, side effects, and comorbidities from electronic health records, event reports, and reports from specific diagnostic tests.<sup id="cite_ref-24" class="reference"><a href="#cite_note-24"><span class="cite-bracket">[</span>24<span class="cite-bracket">]</span></a></sup> One online text mining application in the biomedical literature is <a href="/wiki/PubGene" title="PubGene">PubGene</a>, a publicly accessible <a href="/wiki/Search_engine" title="Search engine">search engine</a> that combines biomedical text mining with network visualization.<sup id="cite_ref-25" class="reference"><a href="#cite_note-25"><span class="cite-bracket">[</span>25<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-26" class="reference"><a href="#cite_note-26"><span class="cite-bracket">[</span>26<span class="cite-bracket">]</span></a></sup> <a href="/wiki/GoPubMed" title="GoPubMed">GoPubMed</a> is a knowledge-based search engine for biomedical texts. Text mining techniques also enable us to extract unknown knowledge from unstructured documents in the clinical domain<sup id="cite_ref-27" class="reference"><a href="#cite_note-27"><span class="cite-bracket">[</span>27<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Software_applications">Software applications</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=6" title="Edit section: Software applications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Text mining methods and software is also being researched and developed by major firms, including <a href="/wiki/IBM" title="IBM">IBM</a> and <a href="/wiki/Microsoft" title="Microsoft">Microsoft</a>, to further automate the mining and analysis processes, and by different firms working in the area of search and indexing in general as a way to improve their results. Within the public sector, much effort has been concentrated on creating software for tracking and monitoring <a href="/wiki/Information_Awareness_Office" title="Information Awareness Office">terrorist activities</a>.<sup id="cite_ref-28" class="reference"><a href="#cite_note-28"><span class="cite-bracket">[</span>28<span class="cite-bracket">]</span></a></sup> For study purposes, <a href="/wiki/Weka_(machine_learning)" class="mw-redirect" title="Weka (machine learning)">Weka software</a> is one of the most popular options in the scientific world, acting as an excellent entry point for beginners. For Python programmers, there is an excellent toolkit called <a href="/wiki/Natural_Language_Toolkit" title="Natural Language Toolkit">NLTK</a> for more general purposes. For more advanced programmers, there's also the <a href="/wiki/Gensim" title="Gensim">Gensim</a> library, which focuses on word embedding-based text representations. </p> <div class="mw-heading mw-heading3"><h3 id="Online_media_applications">Online media applications</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=7" title="Edit section: Online media applications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Text mining is being used by large media companies, such as the <a href="/wiki/Tribune_Company" class="mw-redirect" title="Tribune Company">Tribune Company</a>, to clarify information and to provide readers with greater search experiences, which in turn increases site "stickiness" and revenue. Additionally, on the back end, editors are benefiting by being able to share, associate and package news across properties, significantly increasing opportunities to monetize content. </p> <div class="mw-heading mw-heading3"><h3 id="Business_and_marketing_applications">Business and marketing applications</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=8" title="Edit section: Business and marketing applications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Text analytics is being used in business, particularly, in marketing, such as in <a href="/wiki/Customer_relationship_management" title="Customer relationship management">customer relationship management</a>.<sup id="cite_ref-Text_Analytics:_The_Why_Behind_the_Score_29-0" class="reference"><a href="#cite_note-Text_Analytics:_The_Why_Behind_the_Score-29"><span class="cite-bracket">[</span>29<span class="cite-bracket">]</span></a></sup> Coussement and Van den Poel (2008)<sup id="cite_ref-10.1016/j.im.2008.01.005_30-0" class="reference"><a href="#cite_note-10.1016/j.im.2008.01.005-30"><span class="cite-bracket">[</span>30<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-31" class="reference"><a href="#cite_note-31"><span class="cite-bracket">[</span>31<span class="cite-bracket">]</span></a></sup> apply it to improve <a href="/wiki/Predictive_analytics" title="Predictive analytics">predictive analytics</a> models for customer churn (<a href="/wiki/Customer_attrition" title="Customer attrition">customer attrition</a>).<sup id="cite_ref-10.1016/j.im.2008.01.005_30-1" class="reference"><a href="#cite_note-10.1016/j.im.2008.01.005-30"><span class="cite-bracket">[</span>30<span class="cite-bracket">]</span></a></sup> Text mining is also being applied in stock returns prediction.<sup id="cite_ref-Galvez2017_32-0" class="reference"><a href="#cite_note-Galvez2017-32"><span class="cite-bracket">[</span>32<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Sentiment_analysis">Sentiment analysis</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=9" title="Edit section: Sentiment analysis"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p><a href="/wiki/Sentiment_analysis" title="Sentiment analysis">Sentiment analysis</a> may involve analysis of products such as movies, books, or hotel reviews for estimating how favorable a review is for the product.<sup id="cite_ref-33" class="reference"><a href="#cite_note-33"><span class="cite-bracket">[</span>33<span class="cite-bracket">]</span></a></sup> Such an analysis may need a labeled data set or labeling of the <a href="/wiki/Affect_(psychology)" title="Affect (psychology)">affectivity</a> of words. Resources for affectivity of words and concepts have been made for <a href="/wiki/WordNet" title="WordNet">WordNet</a><sup id="cite_ref-34" class="reference"><a href="#cite_note-34"><span class="cite-bracket">[</span>34<span class="cite-bracket">]</span></a></sup> and <a href="/wiki/ConceptNet" class="mw-redirect" title="ConceptNet">ConceptNet</a>,<sup id="cite_ref-camnet_35-0" class="reference"><a href="#cite_note-camnet-35"><span class="cite-bracket">[</span>35<span class="cite-bracket">]</span></a></sup> respectively. </p><p>Text has been used to detect emotions in the related area of affective computing.<sup id="cite_ref-36" class="reference"><a href="#cite_note-36"><span class="cite-bracket">[</span>36<span class="cite-bracket">]</span></a></sup> Text based approaches to affective computing have been used on multiple corpora such as students evaluations, children stories and news stories. </p> <div class="mw-heading mw-heading3"><h3 id="Scientific_literature_mining_and_academic_applications">Scientific literature mining and academic applications</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=10" title="Edit section: Scientific literature mining and academic applications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The issue of text mining is of importance to publishers who hold large <a href="/wiki/Database" title="Database">databases</a> of information needing <a href="/wiki/Index_(database)" class="mw-redirect" title="Index (database)">indexing</a> for retrieval. This is especially true in scientific disciplines, in which highly specific information is often contained within the written text. Therefore, initiatives have been taken such as <a href="/wiki/Nature_(journal)" title="Nature (journal)">Nature's</a> proposal for an Open Text Mining Interface (OTMI) and the <a href="/wiki/National_Institutes_of_Health" title="National Institutes of Health">National Institutes of Health</a>'s common Journal Publishing <a href="/wiki/Document_Type_Definition" class="mw-redirect" title="Document Type Definition">Document Type Definition</a> (DTD) that would provide semantic cues to machines to answer specific queries contained within the text without removing publisher barriers to public access. </p><p>Academic institutions have also become involved in the text mining initiative: </p> <ul><li>The <a href="/wiki/National_Centre_for_Text_Mining" title="National Centre for Text Mining">National Centre for Text Mining</a> (NaCTeM), is the first publicly funded text mining centre in the world. NaCTeM is operated by the <a href="/wiki/University_of_Manchester" title="University of Manchester">University of Manchester</a><sup id="cite_ref-37" class="reference"><a href="#cite_note-37"><span class="cite-bracket">[</span>37<span class="cite-bracket">]</span></a></sup> in close collaboration with the Tsujii Lab,<sup id="cite_ref-38" class="reference"><a href="#cite_note-38"><span class="cite-bracket">[</span>38<span class="cite-bracket">]</span></a></sup> <a href="/wiki/University_of_Tokyo" title="University of Tokyo">University of Tokyo</a>.<sup id="cite_ref-39" class="reference"><a href="#cite_note-39"><span class="cite-bracket">[</span>39<span class="cite-bracket">]</span></a></sup> NaCTeM provides customised tools, research facilities and offers advice to the academic community. They are funded by the <a href="/wiki/Joint_Information_Systems_Committee" class="mw-redirect" title="Joint Information Systems Committee">Joint Information Systems Committee</a> (JISC) and two of the UK <a href="/wiki/Research_council_(United_Kingdom)" class="mw-redirect" title="Research council (United Kingdom)">research councils</a> (<a href="/wiki/EPSRC" class="mw-redirect" title="EPSRC">EPSRC</a> & <a href="/wiki/BBSRC" class="mw-redirect" title="BBSRC">BBSRC</a>). With an initial focus on text mining in the <a href="/wiki/Biology" title="Biology">biological</a> and <a href="/wiki/Biomedical" class="mw-redirect" title="Biomedical">biomedical</a> sciences, research has since expanded into the areas of <a href="/wiki/Social_sciences" class="mw-redirect" title="Social sciences">social sciences</a>.</li> <li>In the United States, the <a href="/wiki/UC_Berkeley_School_of_Information" title="UC Berkeley School of Information">School of Information</a> at <a href="/wiki/University_of_California,_Berkeley" title="University of California, Berkeley">University of California, Berkeley</a> is developing a program called BioText to assist <a href="/wiki/Biology" title="Biology">biology</a> researchers in text mining and analysis.</li> <li>The <a href="/wiki/Text_Analysis_Portal_for_Research" title="Text Analysis Portal for Research">Text Analysis Portal for Research</a> (TAPoR), currently housed at the <a href="/wiki/University_of_Alberta" title="University of Alberta">University of Alberta</a>, is a scholarly project to catalogue text analysis applications and create a gateway for researchers new to the practice.</li></ul> <div class="mw-heading mw-heading4"><h4 id="Methods_for_scientific_literature_mining">Methods for scientific literature mining</h4><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=11" title="Edit section: Methods for scientific literature mining"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Computational methods have been developed to assist with information retrieval from scientific literature. Published approaches include methods for searching,<sup id="cite_ref-40" class="reference"><a href="#cite_note-40"><span class="cite-bracket">[</span>40<span class="cite-bracket">]</span></a></sup> determining novelty,<sup id="cite_ref-41" class="reference"><a href="#cite_note-41"><span class="cite-bracket">[</span>41<span class="cite-bracket">]</span></a></sup> and clarifying <a href="/wiki/Homonym" title="Homonym">homonyms</a><sup id="cite_ref-42" class="reference"><a href="#cite_note-42"><span class="cite-bracket">[</span>42<span class="cite-bracket">]</span></a></sup> among technical reports. </p> <div class="mw-heading mw-heading3"><h3 id="Digital_humanities_and_computational_sociology">Digital humanities and computational sociology</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=12" title="Edit section: Digital humanities and computational sociology"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The automatic analysis of vast textual corpora has created the possibility for scholars to analyze millions of documents in multiple languages with very limited manual intervention. Key enabling technologies have been parsing, <a href="/wiki/Machine_translation" title="Machine translation">machine translation</a>, topic <a href="/wiki/Categorization" class="mw-redirect" title="Categorization">categorization</a>, and machine learning. </p> <figure class="mw-default-size mw-halign-right" typeof="mw:File/Thumb"><a href="/wiki/File:Tripletsnew2012.png" class="mw-file-description"><img src="//upload.wikimedia.org/wikipedia/commons/thumb/4/43/Tripletsnew2012.png/220px-Tripletsnew2012.png" decoding="async" width="220" height="235" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/4/43/Tripletsnew2012.png/330px-Tripletsnew2012.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/4/43/Tripletsnew2012.png/440px-Tripletsnew2012.png 2x" data-file-width="538" data-file-height="574" /></a><figcaption>Narrative network of US Elections 2012<sup id="cite_ref-ReferenceA_43-0" class="reference"><a href="#cite_note-ReferenceA-43"><span class="cite-bracket">[</span>43<span class="cite-bracket">]</span></a></sup></figcaption></figure> <p>The automatic parsing of textual corpora has enabled the extraction of actors and their relational networks on a vast scale, turning textual data into network data. The resulting networks, which can contain thousands of nodes, are then analyzed by using tools from network theory to identify the key actors, the key communities or parties, and general properties such as robustness or structural stability of the overall network, or centrality of certain nodes.<sup id="cite_ref-44" class="reference"><a href="#cite_note-44"><span class="cite-bracket">[</span>44<span class="cite-bracket">]</span></a></sup> This automates the approach introduced by quantitative narrative analysis,<sup id="cite_ref-45" class="reference"><a href="#cite_note-45"><span class="cite-bracket">[</span>45<span class="cite-bracket">]</span></a></sup> whereby <a href="/wiki/Subject-verb-object" class="mw-redirect" title="Subject-verb-object">subject-verb-object</a> triplets are identified with pairs of actors linked by an action, or pairs formed by actor-object.<sup id="cite_ref-ReferenceA_43-1" class="reference"><a href="#cite_note-ReferenceA-43"><span class="cite-bracket">[</span>43<span class="cite-bracket">]</span></a></sup> </p><p><a href="/wiki/Content_analysis" title="Content analysis">Content analysis</a> has been a traditional part of social sciences and media studies for a long time. The automation of content analysis has allowed a "<a href="/wiki/Big_data" title="Big data">big data</a>" revolution to take place in that field, with studies in social media and newspaper content that include millions of news items. <a href="/wiki/Gender_bias" class="mw-redirect" title="Gender bias">Gender bias</a>, <a href="/wiki/Readability" title="Readability">readability</a>, content similarity, reader preferences, and even mood have been analyzed based on text mining methods over millions of documents.<sup id="cite_ref-46" class="reference"><a href="#cite_note-46"><span class="cite-bracket">[</span>46<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-47" class="reference"><a href="#cite_note-47"><span class="cite-bracket">[</span>47<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-48" class="reference"><a href="#cite_note-48"><span class="cite-bracket">[</span>48<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-49" class="reference"><a href="#cite_note-49"><span class="cite-bracket">[</span>49<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-50" class="reference"><a href="#cite_note-50"><span class="cite-bracket">[</span>50<span class="cite-bracket">]</span></a></sup> The analysis of readability, gender bias and topic bias was demonstrated in Flaounas et al.<sup id="cite_ref-51" class="reference"><a href="#cite_note-51"><span class="cite-bracket">[</span>51<span class="cite-bracket">]</span></a></sup> showing how different topics have different gender biases and levels of readability; the possibility to detect mood patterns in a vast population by analyzing Twitter content was demonstrated as well.<sup id="cite_ref-52" class="reference"><a href="#cite_note-52"><span class="cite-bracket">[</span>52<span class="cite-bracket">]</span></a></sup><sup id="cite_ref-53" class="reference"><a href="#cite_note-53"><span class="cite-bracket">[</span>53<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Software">Software</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=13" title="Edit section: Software"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1236090951"><div role="note" class="hatnote navigation-not-searchable">Main article: <a href="/wiki/List_of_text_mining_software" title="List of text mining software">List of text mining software</a></div> <p>Text mining computer programs are available from many <a href="/wiki/Commercial_software" title="Commercial software">commercial</a> and <a href="/wiki/Open_source" title="Open source">open source</a> companies and sources. </p> <div class="mw-heading mw-heading2"><h2 id="Intellectual_property_law">Intellectual property law</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=14" title="Edit section: Intellectual property law"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <div class="mw-heading mw-heading3"><h3 id="Situation_in_Europe">Situation in Europe</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=15" title="Edit section: Situation in Europe"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <figure class="mw-default-size" typeof="mw:File/Thumb"><span><video id="mwe_player_0" poster="//upload.wikimedia.org/wikipedia/commons/thumb/1/15/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm/220px--FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm.jpg" controls="" preload="none" data-mw-tmh="" class="mw-file-element" width="220" height="124" data-durationhint="232" data-mwtitle="FixCopyright-_Copyright_&_Research_-_Text_&_Data_Mining_(TDM)_Explained.webm" data-mwprovider="wikimediacommons" resource="/wiki/File:FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_(TDM)_Explained.webm"><source src="//upload.wikimedia.org/wikipedia/commons/transcoded/1/15/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm.480p.vp9.webm" type="video/webm; codecs="vp9, opus"" data-transcodekey="480p.vp9.webm" data-width="854" data-height="480" /><source src="//upload.wikimedia.org/wikipedia/commons/transcoded/1/15/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm.720p.vp9.webm" type="video/webm; codecs="vp9, opus"" data-transcodekey="720p.vp9.webm" data-width="1280" data-height="720" /><source src="//upload.wikimedia.org/wikipedia/commons/transcoded/1/15/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm.1080p.vp9.webm" type="video/webm; codecs="vp9, opus"" data-transcodekey="1080p.vp9.webm" data-width="1920" data-height="1080" /><source src="//upload.wikimedia.org/wikipedia/commons/1/15/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm" type="video/webm; codecs="vp8, vorbis"" data-width="1920" data-height="1080" /><source src="//upload.wikimedia.org/wikipedia/commons/transcoded/1/15/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm.144p.mjpeg.mov" type="video/quicktime" data-transcodekey="144p.mjpeg.mov" data-width="256" data-height="144" /><source src="//upload.wikimedia.org/wikipedia/commons/transcoded/1/15/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm.240p.vp9.webm" type="video/webm; codecs="vp9, opus"" data-transcodekey="240p.vp9.webm" data-width="426" data-height="240" /><source src="//upload.wikimedia.org/wikipedia/commons/transcoded/1/15/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm.360p.vp9.webm" type="video/webm; codecs="vp9, opus"" data-transcodekey="360p.vp9.webm" data-width="640" data-height="360" /><source src="//upload.wikimedia.org/wikipedia/commons/transcoded/1/15/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm/FixCopyright-_Copyright_%26_Research_-_Text_%26_Data_Mining_%28TDM%29_Explained.webm.360p.webm" type="video/webm; codecs="vp8, vorbis"" data-transcodekey="360p.webm" data-width="640" data-height="360" /></video></span><figcaption>Video by Fix Copyright campaign explaining TDM and its copyright issues in the EU, 2016 [3:51]</figcaption></figure> <p>Under <a href="/wiki/Copyright_law_of_the_European_Union" title="Copyright law of the European Union">European copyright</a> and <a href="/wiki/Database_Directive" title="Database Directive">database laws</a>, the mining of in-copyright works (such as by <a href="/wiki/Web_mining" class="mw-redirect" title="Web mining">web mining</a>) without the permission of the copyright owner is illegal. In the UK in 2014, on the recommendation of the <a href="/w/index.php?title=Hargreaves_review&action=edit&redlink=1" class="new" title="Hargreaves review (page does not exist)">Hargreaves review</a>, the government amended copyright law<sup id="cite_ref-54" class="reference"><a href="#cite_note-54"><span class="cite-bracket">[</span>54<span class="cite-bracket">]</span></a></sup> to allow text mining as a <a href="/wiki/Limitations_and_exceptions_to_copyright" title="Limitations and exceptions to copyright">limitation and exception</a>. It was the second country in the world to do so, following <a href="/wiki/Copyright_law_of_Japan" title="Copyright law of Japan">Japan</a>, which introduced a mining-specific exception in 2009. However, owing to the restriction of the <a href="/wiki/Information_Society_Directive" class="mw-redirect" title="Information Society Directive">Information Society Directive</a> (2001), the UK exception only allows content mining for non-commercial purposes. UK copyright law does not allow this provision to be overridden by contractual terms and conditions. </p><p>The <a href="/wiki/European_Commission" title="European Commission">European Commission</a> facilitated stakeholder discussion on text and <a href="/wiki/Data_mining" title="Data mining">data mining</a> in 2013, under the title of Licenses for Europe.<sup id="cite_ref-55" class="reference"><a href="#cite_note-55"><span class="cite-bracket">[</span>55<span class="cite-bracket">]</span></a></sup> The fact that the focus on the solution to this legal issue was licenses, and not limitations and exceptions to copyright law, led representatives of universities, researchers, libraries, civil society groups and <a href="/wiki/Open_access" title="Open access">open access</a> publishers to leave the stakeholder dialogue in May 2013.<sup id="cite_ref-56" class="reference"><a href="#cite_note-56"><span class="cite-bracket">[</span>56<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Situation_in_the_United_States">Situation in the United States</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=16" title="Edit section: Situation in the United States"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p><a href="/wiki/Copyright_law_of_the_United_States" title="Copyright law of the United States">US copyright law</a>, and in particular its <a href="/wiki/Fair_use" title="Fair use">fair use</a> provisions, means that text mining in America, as well as other fair use countries such as Israel, Taiwan and South Korea, is viewed as being legal. As text mining is transformative, meaning that it does not supplant the original work, it is viewed as being lawful under fair use. For example, as part of the <a href="/wiki/Google_Book_Search_Settlement_Agreement" class="mw-redirect" title="Google Book Search Settlement Agreement">Google Book settlement</a> the presiding judge on the case ruled that Google's digitization project of in-copyright books was lawful, in part because of the transformative uses that the digitization project displayed—one such use being text and data mining.<sup id="cite_ref-57" class="reference"><a href="#cite_note-57"><span class="cite-bracket">[</span>57<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading3"><h3 id="Situation_in_Australia">Situation in Australia</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=17" title="Edit section: Situation in Australia"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>There is no exception in <a href="/wiki/Copyright_law_of_Australia" title="Copyright law of Australia">copyright law of Australia</a> for text or data mining within the <i><a href="/wiki/Copyright_Act_1968" class="mw-redirect" title="Copyright Act 1968">Copyright Act 1968</a></i>. The <a href="/wiki/Australian_Law_Reform_Commission" title="Australian Law Reform Commission">Australian Law Reform Commission</a> has noted that it is unlikely that the "research and study" <a href="/wiki/Fair_dealing" title="Fair dealing">fair dealing</a> exception would extend to cover such a topic either, given it would be beyond the "reasonable portion" requirement.<sup id="cite_ref-58" class="reference"><a href="#cite_note-58"><span class="cite-bracket">[</span>58<span class="cite-bracket">]</span></a></sup> </p> <div class="mw-heading mw-heading2"><h2 id="Implications">Implications</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=18" title="Edit section: Implications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Until recently, websites most often used text-based searches, which only found documents containing specific user-defined words or phrases. Now, through use of a <a href="/wiki/Semantic_web" class="mw-redirect" title="Semantic web">semantic web</a>, text mining can find content based on meaning and context (rather than just by a specific word). Additionally, text mining software can be used to build large dossiers of information about specific people and events. For example, large datasets based on data extracted from news reports can be built to facilitate social networks analysis or <a href="/wiki/Counter-intelligence" class="mw-redirect" title="Counter-intelligence">counter-intelligence</a>. In effect, the text mining software may act in a capacity similar to an <a href="/wiki/Intelligence_analyst" class="mw-redirect" title="Intelligence analyst">intelligence analyst</a> or research librarian, albeit with a more limited scope of analysis. Text mining is also used in some email <a href="/wiki/Spam_filter" class="mw-redirect" title="Spam filter">spam filters</a> as a way of determining the characteristics of messages that are likely to be advertisements or other unwanted material. Text mining plays an important role in determining financial <a href="/wiki/Market_sentiment" title="Market sentiment">market sentiment</a>. </p> <div class="mw-heading mw-heading2"><h2 id="See_also">See also</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=19" title="Edit section: See also"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1184024115">.mw-parser-output .div-col{margin-top:0.3em;column-width:30em}.mw-parser-output .div-col-small{font-size:90%}.mw-parser-output .div-col-rules{column-rule:1px solid #aaa}.mw-parser-output .div-col dl,.mw-parser-output .div-col ol,.mw-parser-output .div-col ul{margin-top:0}.mw-parser-output .div-col li,.mw-parser-output .div-col dd{page-break-inside:avoid;break-inside:avoid-column}</style><div class="div-col" style="column-width: 22em;"> <ul><li><a href="/wiki/Concept_mining" title="Concept mining">Concept mining</a></li> <li><a href="/wiki/Document_processing" title="Document processing">Document processing</a></li> <li><a href="/wiki/Full_text_search" class="mw-redirect" title="Full text search">Full text search</a></li> <li><a href="/wiki/List_of_text_mining_software" title="List of text mining software">List of text mining software</a></li> <li><a href="/wiki/Market_sentiment" title="Market sentiment">Market sentiment</a></li> <li><a href="/wiki/Name_resolution_(semantics_and_text_extraction)" title="Name resolution (semantics and text extraction)">Name resolution (semantics and text extraction)</a></li> <li><a href="/wiki/Named_entity_recognition" class="mw-redirect" title="Named entity recognition">Named entity recognition</a></li> <li><a href="/wiki/News_analytics" title="News analytics">News analytics</a></li> <li><a href="/wiki/Ontology_learning" title="Ontology learning">Ontology learning</a></li> <li><a href="/wiki/Record_linkage" title="Record linkage">Record linkage</a></li> <li><a href="/wiki/Sequential_pattern_mining" title="Sequential pattern mining">Sequential pattern mining</a> (string and sequence mining)</li> <li><a href="/wiki/W-shingling" title="W-shingling">w-shingling</a></li> <li><a href="/wiki/Web_mining" class="mw-redirect" title="Web mining">Web mining</a>, a task that may involve text mining (e.g. first find appropriate web pages by classifying crawled web pages, then extract the desired information from the text content of these pages considered relevant)</li></ul> </div> <div class="mw-heading mw-heading2"><h2 id="References">References</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=20" title="Edit section: References"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <div class="mw-heading mw-heading3"><h3 id="Citations">Citations</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=21" title="Edit section: Citations"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <style data-mw-deduplicate="TemplateStyles:r1239543626">.mw-parser-output .reflist{margin-bottom:0.5em;list-style-type:decimal}@media screen{.mw-parser-output .reflist{font-size:90%}}.mw-parser-output .reflist .references{font-size:100%;margin-bottom:0;list-style-type:inherit}.mw-parser-output .reflist-columns-2{column-width:30em}.mw-parser-output .reflist-columns-3{column-width:25em}.mw-parser-output .reflist-columns{margin-top:0.3em}.mw-parser-output .reflist-columns ol{margin-top:0}.mw-parser-output .reflist-columns li{page-break-inside:avoid;break-inside:avoid-column}.mw-parser-output .reflist-upper-alpha{list-style-type:upper-alpha}.mw-parser-output .reflist-upper-roman{list-style-type:upper-roman}.mw-parser-output .reflist-lower-alpha{list-style-type:lower-alpha}.mw-parser-output .reflist-lower-greek{list-style-type:lower-greek}.mw-parser-output .reflist-lower-roman{list-style-type:lower-roman}</style><div class="reflist"> <div class="mw-references-wrap mw-references-columns"><ol class="references"> <li id="cite_note-1"><span class="mw-cite-backlink"><b><a href="#cite_ref-1">^</a></b></span> <span class="reference-text"><style data-mw-deduplicate="TemplateStyles:r1238218222">.mw-parser-output cite.citation{font-style:inherit;word-wrap:break-word}.mw-parser-output .citation q{quotes:"\"""\"""'""'"}.mw-parser-output .citation:target{background-color:rgba(0,127,255,0.133)}.mw-parser-output .id-lock-free.id-lock-free a{background:url("//upload.wikimedia.org/wikipedia/commons/6/65/Lock-green.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-limited.id-lock-limited a,.mw-parser-output .id-lock-registration.id-lock-registration a{background:url("//upload.wikimedia.org/wikipedia/commons/d/d6/Lock-gray-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .id-lock-subscription.id-lock-subscription a{background:url("//upload.wikimedia.org/wikipedia/commons/a/aa/Lock-red-alt-2.svg")right 0.1em center/9px no-repeat}.mw-parser-output .cs1-ws-icon a{background:url("//upload.wikimedia.org/wikipedia/commons/4/4c/Wikisource-logo.svg")right 0.1em center/12px no-repeat}body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-free a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-limited a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-registration a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .id-lock-subscription a,body:not(.skin-timeless):not(.skin-minerva) .mw-parser-output .cs1-ws-icon a{background-size:contain;padding:0 1em 0 0}.mw-parser-output .cs1-code{color:inherit;background:inherit;border:none;padding:inherit}.mw-parser-output .cs1-hidden-error{display:none;color:var(--color-error,#d33)}.mw-parser-output .cs1-visible-error{color:var(--color-error,#d33)}.mw-parser-output .cs1-maint{display:none;color:#085;margin-left:0.3em}.mw-parser-output .cs1-kern-left{padding-left:0.2em}.mw-parser-output .cs1-kern-right{padding-right:0.2em}.mw-parser-output .citation .mw-selflink{font-weight:inherit}@media screen{.mw-parser-output .cs1-format{font-size:95%}html.skin-theme-clientpref-night .mw-parser-output .cs1-maint{color:#18911f}}@media screen and (prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .cs1-maint{color:#18911f}}</style><cite class="citation web cs1"><a rel="nofollow" class="external text" href="http://people.ischool.berkeley.edu/~hearst/text-mining.html">"Marti Hearst: What is Text Mining?"</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=unknown&rft.btitle=Marti+Hearst%3A+What+is+Text+Mining%3F&rft_id=http%3A%2F%2Fpeople.ischool.berkeley.edu%2F~hearst%2Ftext-mining.html&rfr_id=info%3Asid%2Fen.wikipedia.org%3AText+mining" class="Z3988"></span></span> </li> <li id="cite_note-2"><span class="mw-cite-backlink"><b><a href="#cite_ref-2">^</a></b></span> <span class="reference-text">Hotho, A., Nürnberger, A. and Paaß, G. (2005). "A brief survey of text mining". In Ldv Forum, Vol. 20(1), p. 19-62</span> </li> <li id="cite_note-3"><span class="mw-cite-backlink"><b><a href="#cite_ref-3">^</a></b></span> <span class="reference-text">Feldman, R. and Sanger, J. (2007). The text mining handbook. Cambridge University Press. New York</span> </li> <li id="cite_note-4"><span class="mw-cite-backlink"><b><a href="#cite_ref-4">^</a></b></span> <span class="reference-text"><a rel="nofollow" class="external autonumber" href="http://intelligent-enterprise.informationweek.com/blog/archives/2007/02/defining_text_a.html">[1]</a> <a rel="nofollow" class="external text" href="https://web.archive.org/web/20091129171151/http://intelligent-enterprise.informationweek.com/blog/archives/2007/02/defining_text_a.html">Archived</a> November 29, 2009, at the <a href="/wiki/Wayback_Machine" title="Wayback Machine">Wayback Machine</a></span> </li> <li id="cite_note-5"><span class="mw-cite-backlink"><b><a href="#cite_ref-5">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="https://www.cs.cmu.edu/~dunja/CFPWshKDD2000.html">"KDD-2000 Workshop on Text Mining – Call for Papers"</a>. Cs.cmu.edu<span class="reference-accessdate">. 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S Sudhahar, GA Veltri, N Cristianini; Big Data & Society 2 (1), 1-28, 2015</span> </li> <li id="cite_note-44"><span class="mw-cite-backlink"><b><a href="#cite_ref-44">^</a></b></span> <span class="reference-text">Network analysis of narrative content in large corpora; S Sudhahar, G De Fazio, R Franzosi, N Cristianini; Natural Language Engineering, 1-32, 2013</span> </li> <li id="cite_note-45"><span class="mw-cite-backlink"><b><a href="#cite_ref-45">^</a></b></span> <span class="reference-text">Quantitative Narrative Analysis; Roberto Franzosi; Emory University © 2010</span> </li> <li id="cite_note-46"><span class="mw-cite-backlink"><b><a href="#cite_ref-46">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite id="CITEREFLansdall-WelfareSudhaharThompsonLewis2017" class="citation journal cs1">Lansdall-Welfare, Thomas; Sudhahar, Saatviga; Thompson, James; Lewis, Justin; Team, FindMyPast Newspaper; Cristianini, Nello (2017-01-09). <a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5278459">"Content analysis of 150 years of British periodicals"</a>. <i>Proceedings of the National Academy of Sciences</i>. <b>114</b> (4): E457–E465. <a href="/wiki/Bibcode_(identifier)" class="mw-redirect" title="Bibcode (identifier)">Bibcode</a>:<a rel="nofollow" class="external text" href="https://ui.adsabs.harvard.edu/abs/2017PNAS..114E.457L">2017PNAS..114E.457L</a>. <a href="/wiki/Doi_(identifier)" class="mw-redirect" title="Doi (identifier)">doi</a>:<span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://doi.org/10.1073%2Fpnas.1606380114">10.1073/pnas.1606380114</a></span>. <a href="/wiki/ISSN_(identifier)" class="mw-redirect" title="ISSN (identifier)">ISSN</a> <a rel="nofollow" class="external text" href="https://search.worldcat.org/issn/0027-8424">0027-8424</a>. <a href="/wiki/PMC_(identifier)" class="mw-redirect" title="PMC (identifier)">PMC</a> <span class="id-lock-free" title="Freely accessible"><a rel="nofollow" class="external text" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5278459">5278459</a></span>. <a href="/wiki/PMID_(identifier)" class="mw-redirect" title="PMID (identifier)">PMID</a> <a rel="nofollow" class="external text" href="https://pubmed.ncbi.nlm.nih.gov/28069962">28069962</a>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Proceedings+of+the+National+Academy+of+Sciences&rft.atitle=Content+analysis+of+150+years+of+British+periodicals&rft.volume=114&rft.issue=4&rft.pages=E457-E465&rft.date=2017-01-09&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC5278459%23id-name%3DPMC&rft_id=info%3Abibcode%2F2017PNAS..114E.457L&rft_id=info%3Apmid%2F28069962&rft_id=info%3Adoi%2F10.1073%2Fpnas.1606380114&rft.issn=0027-8424&rft.aulast=Lansdall-Welfare&rft.aufirst=Thomas&rft.au=Sudhahar%2C+Saatviga&rft.au=Thompson%2C+James&rft.au=Lewis%2C+Justin&rft.au=Team%2C+FindMyPast+Newspaper&rft.au=Cristianini%2C+Nello&rft_id=https%3A%2F%2Fwww.ncbi.nlm.nih.gov%2Fpmc%2Farticles%2FPMC5278459&rfr_id=info%3Asid%2Fen.wikipedia.org%3AText+mining" class="Z3988"></span></span> </li> <li id="cite_note-47"><span class="mw-cite-backlink"><b><a href="#cite_ref-47">^</a></b></span> <span class="reference-text">I. 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Retrieved <span class="nowrap">14 November</span> 2014</span>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=unknown&rft.jtitle=European+Commission&rft.atitle=Licences+for+Europe+%E2%80%93+Structured+Stakeholder+Dialogue+2013&rft_id=http%3A%2F%2Fec.europa.eu%2Flicences-for-europe-dialogue%2Fen%2Fcontent%2Fabout-site&rfr_id=info%3Asid%2Fen.wikipedia.org%3AText+mining" class="Z3988"></span></span> </li> <li id="cite_note-56"><span class="mw-cite-backlink"><b><a href="#cite_ref-56">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="https://web.archive.org/web/20141129021244/http://libereurope.eu/news/text-and-data-mining-its-importance-and-the-need-for-change-in-europe/">"Text and Data Mining:Its importance and the need for change in Europe"</a>. <i><a href="/wiki/Association_of_European_Research_Libraries" title="Association of European Research Libraries">Association of European Research Libraries</a></i>. 2013-04-25. Archived from <a rel="nofollow" class="external text" href="http://libereurope.eu/news/text-and-data-mining-its-importance-and-the-need-for-change-in-europe/">the original</a> on 2014-11-29<span class="reference-accessdate">. Retrieved <span class="nowrap">14 November</span> 2014</span>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=unknown&rft.jtitle=Association+of+European+Research+Libraries&rft.atitle=Text+and+Data+Mining%3AIts+importance+and+the+need+for+change+in+Europe&rft.date=2013-04-25&rft_id=http%3A%2F%2Flibereurope.eu%2Fnews%2Ftext-and-data-mining-its-importance-and-the-need-for-change-in-europe%2F&rfr_id=info%3Asid%2Fen.wikipedia.org%3AText+mining" class="Z3988"></span></span> </li> <li id="cite_note-57"><span class="mw-cite-backlink"><b><a href="#cite_ref-57">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite class="citation news cs1"><a rel="nofollow" class="external text" href="http://www.lexology.com/library/detail.aspx?g=a18c5b92-5a20-4d1d-a098-a3095046a88e">"Judge grants summary judgment in favor of Google Books – a fair use victory"</a>. <i>Lexology</i>. Antonelli Law Ltd. 19 November 2013<span class="reference-accessdate">. Retrieved <span class="nowrap">14 November</span> 2014</span>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.jtitle=Lexology&rft.atitle=Judge+grants+summary+judgment+in+favor+of+Google+Books+%E2%80%93+a+fair+use+victory&rft.date=2013-11-19&rft_id=http%3A%2F%2Fwww.lexology.com%2Flibrary%2Fdetail.aspx%3Fg%3Da18c5b92-5a20-4d1d-a098-a3095046a88e&rfr_id=info%3Asid%2Fen.wikipedia.org%3AText+mining" class="Z3988"></span></span> </li> <li id="cite_note-58"><span class="mw-cite-backlink"><b><a href="#cite_ref-58">^</a></b></span> <span class="reference-text"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><cite class="citation web cs1"><a rel="nofollow" class="external text" href="https://www.alrc.gov.au/publication/copyright-and-the-digital-economy-dp-79/8-non-consumptive-use/text-and-data-mining/">"Text and data mining"</a>. <i><a href="/wiki/Australian_Law_Reform_Commission" title="Australian Law Reform Commission">Australian Law Reform Commission</a></i>. 4 June 2013<span class="reference-accessdate">. Retrieved <span class="nowrap">10 February</span> 2023</span>.</cite><span title="ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=unknown&rft.jtitle=Australian+Law+Reform+Commission&rft.atitle=Text+and+data+mining&rft.date=2013-06-04&rft_id=https%3A%2F%2Fwww.alrc.gov.au%2Fpublication%2Fcopyright-and-the-digital-economy-dp-79%2F8-non-consumptive-use%2Ftext-and-data-mining%2F&rfr_id=info%3Asid%2Fen.wikipedia.org%3AText+mining" class="Z3988"></span></span> </li> </ol></div></div> <div class="mw-heading mw-heading3"><h3 id="Sources">Sources</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=22" title="Edit section: Sources"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li>Ananiadou, S. and McNaught, J. (Editors) (2006). <i>Text Mining for Biology and Biomedicine</i>. Artech House Books. <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-1-58053-984-5" title="Special:BookSources/978-1-58053-984-5">978-1-58053-984-5</a></li> <li>Bilisoly, R. (2008). <i>Practical Text Mining with Perl</i>. New York: John Wiley & Sons. <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-0-470-17643-6" title="Special:BookSources/978-0-470-17643-6">978-0-470-17643-6</a></li> <li>Feldman, R., and Sanger, J. (2006). <i>The Text Mining Handbook</i>. New York: Cambridge University Press. <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-0-521-83657-9" title="Special:BookSources/978-0-521-83657-9">978-0-521-83657-9</a></li> <li>Hotho, A., Nürnberger, A. and Paaß, G. (2005). "A brief survey of text mining". In Ldv Forum, Vol. 20(1), p. 19-62</li> <li>Indurkhya, N., and Damerau, F. (2010). <i>Handbook of Natural Language Processing</i>, 2nd Edition. Boca Raton, FL: CRC Press. <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-1-4200-8592-1" title="Special:BookSources/978-1-4200-8592-1">978-1-4200-8592-1</a></li> <li>Kao, A., and Poteet, S. (Editors). <i>Natural Language Processing and Text Mining</i>. Springer. <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/1-84628-175-X" title="Special:BookSources/1-84628-175-X">1-84628-175-X</a></li> <li>Konchady, M. <i>Text Mining Application Programming (Programming Series)</i>. Charles River Media. <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/1-58450-460-9" title="Special:BookSources/1-58450-460-9">1-58450-460-9</a></li> <li>Manning, C., and Schutze, H. (1999). <i>Foundations of Statistical Natural Language Processing</i>. Cambridge, MA: MIT Press. <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-0-262-13360-9" title="Special:BookSources/978-0-262-13360-9">978-0-262-13360-9</a></li> <li>Miner, G., Elder, J., Hill. T, Nisbet, R., Delen, D. and Fast, A. (2012). <i>Practical Text Mining and Statistical Analysis for Non-structured Text Data Applications</i>. Elsevier Academic Press. <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-0-12-386979-1" title="Special:BookSources/978-0-12-386979-1">978-0-12-386979-1</a></li> <li>McKnight, W. (2005). "Building business intelligence: Text data mining in business intelligence". <i>DM Review</i>, 21–22.</li> <li>Srivastava, A., and Sahami. M. (2009). <i>Text Mining: Classification, Clustering, and Applications</i>. Boca Raton, FL: CRC Press. <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-1-4200-5940-3" title="Special:BookSources/978-1-4200-5940-3">978-1-4200-5940-3</a></li> <li>Zanasi, A. (Editor) (2007). <i>Text Mining and its Applications to Intelligence, CRM and Knowledge Management</i>. WIT Press. <link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1238218222"><a href="/wiki/ISBN_(identifier)" class="mw-redirect" title="ISBN (identifier)">ISBN</a> <a href="/wiki/Special:BookSources/978-1-84564-131-3" title="Special:BookSources/978-1-84564-131-3">978-1-84564-131-3</a></li></ul> <div class="mw-heading mw-heading2"><h2 id="External_links">External links</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Text_mining&action=edit&section=23" title="Edit section: External links"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a rel="nofollow" class="external text" href="http://people.ischool.berkeley.edu/~hearst/text-mining.html">Marti Hearst: What Is Text Mining?</a> (October 2003)</li> <li><a rel="nofollow" class="external text" href="http://projects.ldc.upenn.edu/ace/">Automatic Content Extraction, Linguistic Data Consortium</a> <a rel="nofollow" class="external text" href="https://web.archive.org/web/20130925194420/http://projects.ldc.upenn.edu/ace/">Archived</a> 2013-09-25 at the <a href="/wiki/Wayback_Machine" title="Wayback Machine">Wayback Machine</a></li> <li><a rel="nofollow" class="external text" href="https://web.archive.org/web/20060308054306/http://www.itl.nist.gov/iad/894.01/tests/ace/">Automatic Content Extraction, NIST</a></li></ul> <div class="navbox-styles"><style data-mw-deduplicate="TemplateStyles:r1129693374">.mw-parser-output .hlist dl,.mw-parser-output .hlist ol,.mw-parser-output .hlist ul{margin:0;padding:0}.mw-parser-output .hlist dd,.mw-parser-output .hlist dt,.mw-parser-output .hlist li{margin:0;display:inline}.mw-parser-output .hlist.inline,.mw-parser-output .hlist.inline dl,.mw-parser-output .hlist.inline ol,.mw-parser-output .hlist.inline ul,.mw-parser-output .hlist dl dl,.mw-parser-output .hlist dl ol,.mw-parser-output .hlist dl ul,.mw-parser-output .hlist ol dl,.mw-parser-output .hlist ol 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.navbox{display:none!important}}</style></div><div role="navigation" class="navbox" aria-labelledby="Natural_language_processing" style="padding:3px"><table class="nowraplinks hlist mw-collapsible autocollapse navbox-inner" style="border-spacing:0;background:transparent;color:inherit"><tbody><tr><th scope="col" class="navbox-title" colspan="2"><link rel="mw-deduplicated-inline-style" href="mw-data:TemplateStyles:r1129693374"><style data-mw-deduplicate="TemplateStyles:r1239400231">.mw-parser-output .navbar{display:inline;font-size:88%;font-weight:normal}.mw-parser-output .navbar-collapse{float:left;text-align:left}.mw-parser-output .navbar-boxtext{word-spacing:0}.mw-parser-output .navbar ul{display:inline-block;white-space:nowrap;line-height:inherit}.mw-parser-output .navbar-brackets::before{margin-right:-0.125em;content:"[ "}.mw-parser-output .navbar-brackets::after{margin-left:-0.125em;content:" ]"}.mw-parser-output .navbar li{word-spacing:-0.125em}.mw-parser-output .navbar a>span,.mw-parser-output .navbar a>abbr{text-decoration:inherit}.mw-parser-output .navbar-mini abbr{font-variant:small-caps;border-bottom:none;text-decoration:none;cursor:inherit}.mw-parser-output .navbar-ct-full{font-size:114%;margin:0 7em}.mw-parser-output .navbar-ct-mini{font-size:114%;margin:0 4em}html.skin-theme-clientpref-night .mw-parser-output .navbar li a abbr{color:var(--color-base)!important}@media(prefers-color-scheme:dark){html.skin-theme-clientpref-os .mw-parser-output .navbar li a abbr{color:var(--color-base)!important}}@media print{.mw-parser-output .navbar{display:none!important}}</style><div class="navbar plainlinks hlist navbar-mini"><ul><li class="nv-view"><a href="/wiki/Template:Natural_language_processing" title="Template:Natural language processing"><abbr title="View this template">v</abbr></a></li><li class="nv-talk"><a href="/wiki/Template_talk:Natural_language_processing" title="Template talk:Natural language processing"><abbr title="Discuss this template">t</abbr></a></li><li class="nv-edit"><a href="/wiki/Special:EditPage/Template:Natural_language_processing" title="Special:EditPage/Template:Natural language processing"><abbr title="Edit this template">e</abbr></a></li></ul></div><div id="Natural_language_processing" style="font-size:114%;margin:0 4em"><a href="/wiki/Natural_language_processing" title="Natural language processing">Natural language processing</a></div></th></tr><tr><th scope="row" class="navbox-group" style="width:1%">General terms</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/AI-complete" title="AI-complete">AI-complete</a></li> <li><a href="/wiki/Bag-of-words_model" title="Bag-of-words model">Bag-of-words</a></li> <li><a href="/wiki/N-gram" title="N-gram">n-gram</a> <ul><li><a href="/wiki/Bigram" title="Bigram">Bigram</a></li> <li><a href="/wiki/Trigram" title="Trigram">Trigram</a></li></ul></li> <li><a href="/wiki/Computational_linguistics" title="Computational linguistics">Computational linguistics</a></li> <li><a href="/wiki/Natural_language_understanding" title="Natural language understanding">Natural language understanding</a></li> <li><a href="/wiki/Stop_word" title="Stop word">Stop words</a></li> <li><a href="/wiki/Text_processing" title="Text processing">Text processing</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a class="mw-selflink selflink">Text analysis</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Argument_mining" title="Argument mining">Argument mining</a></li> <li><a href="/wiki/Collocation_extraction" title="Collocation extraction">Collocation extraction</a></li> <li><a href="/wiki/Concept_mining" title="Concept mining">Concept mining</a></li> <li><a href="/wiki/Coreference#Coreference_resolution" title="Coreference">Coreference resolution</a></li> <li><a href="/wiki/Deep_linguistic_processing" title="Deep linguistic processing">Deep linguistic processing</a></li> <li><a href="/wiki/Distant_reading" title="Distant reading">Distant reading</a></li> <li><a href="/wiki/Information_extraction" title="Information extraction">Information extraction</a></li> <li><a href="/wiki/Named-entity_recognition" title="Named-entity recognition">Named-entity recognition</a></li> <li><a href="/wiki/Ontology_learning" title="Ontology learning">Ontology learning</a></li> <li><a href="/wiki/Parsing" title="Parsing">Parsing</a> <ul><li><a href="/wiki/Semantic_parsing" title="Semantic parsing">Semantic parsing</a></li> <li><a href="/wiki/Syntactic_parsing_(computational_linguistics)" title="Syntactic parsing (computational linguistics)">Syntactic parsing</a></li></ul></li> <li><a href="/wiki/Part-of-speech_tagging" title="Part-of-speech tagging">Part-of-speech tagging</a></li> <li><a href="/wiki/Semantic_analysis_(machine_learning)" title="Semantic analysis (machine learning)">Semantic analysis</a></li> <li><a href="/wiki/Semantic_role_labeling" title="Semantic role labeling">Semantic role labeling</a></li> <li><a href="/wiki/Semantic_decomposition_(natural_language_processing)" title="Semantic decomposition (natural language processing)">Semantic decomposition</a></li> <li><a href="/wiki/Semantic_similarity" title="Semantic similarity">Semantic similarity</a></li> <li><a href="/wiki/Sentiment_analysis" title="Sentiment analysis">Sentiment analysis</a></li></ul> <ul><li><a href="/wiki/Terminology_extraction" title="Terminology extraction">Terminology extraction</a></li> <li><a class="mw-selflink selflink">Text mining</a></li> <li><a href="/wiki/Textual_entailment" title="Textual entailment">Textual entailment</a></li> <li><a href="/wiki/Truecasing" title="Truecasing">Truecasing</a></li> <li><a href="/wiki/Word-sense_disambiguation" title="Word-sense disambiguation">Word-sense disambiguation</a></li> <li><a href="/wiki/Word-sense_induction" title="Word-sense induction">Word-sense induction</a></li></ul> </div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th id="Text_segmentation" scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Text_segmentation" title="Text segmentation">Text segmentation</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Compound-term_processing" title="Compound-term processing">Compound-term processing</a></li> <li><a href="/wiki/Lemmatisation" class="mw-redirect" title="Lemmatisation">Lemmatisation</a></li> <li><a href="/wiki/Lexical_analysis" title="Lexical analysis">Lexical analysis</a></li> <li><a href="/wiki/Shallow_parsing" title="Shallow parsing">Text chunking</a></li> <li><a href="/wiki/Stemming" title="Stemming">Stemming</a></li> <li><a href="/wiki/Sentence_boundary_disambiguation" title="Sentence boundary disambiguation">Sentence segmentation</a></li> <li><a href="/wiki/Word#Word_boundaries" title="Word">Word segmentation</a></li></ul> </div></td></tr></tbody></table><div> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Automatic_summarization" title="Automatic summarization">Automatic summarization</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Multi-document_summarization" title="Multi-document summarization">Multi-document summarization</a></li> <li><a href="/wiki/Sentence_extraction" title="Sentence extraction">Sentence extraction</a></li> <li><a href="/wiki/Text_simplification" title="Text simplification">Text simplification</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Machine_translation" title="Machine translation">Machine translation</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Computer-assisted_translation" title="Computer-assisted translation">Computer-assisted</a></li> <li><a href="/wiki/Example-based_machine_translation" title="Example-based machine translation">Example-based</a></li> <li><a href="/wiki/Rule-based_machine_translation" title="Rule-based machine translation">Rule-based</a></li> <li><a href="/wiki/Statistical_machine_translation" title="Statistical machine translation">Statistical</a></li> <li><a href="/wiki/Transfer-based_machine_translation" title="Transfer-based machine translation">Transfer-based</a></li> <li><a href="/wiki/Neural_machine_translation" title="Neural machine translation">Neural</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Distributional_semantics" title="Distributional semantics">Distributional semantics</a> models</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/BERT_(language_model)" title="BERT (language model)">BERT</a></li> <li><a href="/wiki/Document-term_matrix" title="Document-term matrix">Document-term matrix</a></li> <li><a href="/wiki/Explicit_semantic_analysis" title="Explicit semantic analysis">Explicit semantic analysis</a></li> <li><a href="/wiki/FastText" title="FastText">fastText</a></li> <li><a href="/wiki/GloVe" title="GloVe">GloVe</a></li> <li><a href="/wiki/Language_model" title="Language model">Language model</a> (<a href="/wiki/Large_language_model" title="Large language model">large</a>)</li> <li><a href="/wiki/Latent_semantic_analysis" title="Latent semantic analysis">Latent semantic analysis</a></li> <li><a href="/wiki/Seq2seq" title="Seq2seq">Seq2seq</a></li> <li><a href="/wiki/Word_embedding" title="Word embedding">Word embedding</a></li> <li><a href="/wiki/Word2vec" title="Word2vec">Word2vec</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Language_resource" title="Language resource">Language resources</a>,<br />datasets and corpora</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"></div><table class="nowraplinks navbox-subgroup" style="border-spacing:0"><tbody><tr><th scope="row" class="navbox-group" style="width:1%">Types and<br />standards</th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Corpus_linguistics" title="Corpus linguistics">Corpus linguistics</a></li> <li><a href="/wiki/Lexical_resource" title="Lexical resource">Lexical resource</a></li> <li><a href="/wiki/Linguistic_Linked_Open_Data" title="Linguistic Linked Open Data">Linguistic Linked Open Data</a></li> <li><a href="/wiki/Machine-readable_dictionary" title="Machine-readable dictionary">Machine-readable dictionary</a></li> <li><a href="/wiki/Parallel_text" title="Parallel text">Parallel text</a></li> <li><a href="/wiki/PropBank" title="PropBank">PropBank</a></li> <li><a href="/wiki/Semantic_network" title="Semantic network">Semantic network</a></li> <li><a href="/wiki/Simple_Knowledge_Organization_System" title="Simple Knowledge Organization System">Simple Knowledge Organization System</a></li> <li><a href="/wiki/Speech_corpus" title="Speech corpus">Speech corpus</a></li> <li><a href="/wiki/Text_corpus" title="Text corpus">Text corpus</a></li> <li><a href="/wiki/Thesaurus_(information_retrieval)" title="Thesaurus (information retrieval)">Thesaurus (information retrieval)</a></li> <li><a href="/wiki/Treebank" title="Treebank">Treebank</a></li> <li><a href="/wiki/Universal_Dependencies" title="Universal Dependencies">Universal Dependencies</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Data</th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/BabelNet" title="BabelNet">BabelNet</a></li> <li><a href="/wiki/Bank_of_English" title="Bank of English">Bank of English</a></li> <li><a href="/wiki/DBpedia" title="DBpedia">DBpedia</a></li> <li><a href="/wiki/FrameNet" title="FrameNet">FrameNet</a></li> <li><a href="/wiki/Google_Ngram_Viewer" class="mw-redirect" title="Google Ngram Viewer">Google Ngram Viewer</a></li> <li><a href="/wiki/UBY" title="UBY">UBY</a></li> <li><a href="/wiki/WordNet" title="WordNet">WordNet</a></li> <li><a href="/wiki/Wikidata" title="Wikidata">Wikidata</a></li></ul> </div></td></tr></tbody></table><div></div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Automatic_identification_and_data_capture" title="Automatic identification and data capture">Automatic identification<br />and data capture</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Speech_recognition" title="Speech recognition">Speech recognition</a></li> <li><a href="/wiki/Speech_segmentation" title="Speech segmentation">Speech segmentation</a></li> <li><a href="/wiki/Speech_synthesis" title="Speech synthesis">Speech synthesis</a></li> <li><a href="/wiki/Natural_language_generation" title="Natural language generation">Natural language generation</a></li> <li><a href="/wiki/Optical_character_recognition" title="Optical character recognition">Optical character recognition</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Topic_model" title="Topic model">Topic model</a></th><td class="navbox-list-with-group navbox-list navbox-even" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Document_classification" title="Document classification">Document classification</a></li> <li><a href="/wiki/Latent_Dirichlet_allocation" title="Latent Dirichlet allocation">Latent Dirichlet allocation</a></li> <li><a href="/wiki/Pachinko_allocation" title="Pachinko allocation">Pachinko allocation</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Computer-assisted_reviewing" title="Computer-assisted reviewing">Computer-assisted<br />reviewing</a></th><td class="navbox-list-with-group navbox-list navbox-odd" style="width:100%;padding:0"><div style="padding:0 0.25em"> <ul><li><a href="/wiki/Automated_essay_scoring" title="Automated essay scoring">Automated essay scoring</a></li> <li><a href="/wiki/Concordancer" title="Concordancer">Concordancer</a></li> <li><a href="/wiki/Grammar_checker" title="Grammar checker">Grammar checker</a></li> <li><a href="/wiki/Predictive_text" title="Predictive text">Predictive text</a></li> <li><a href="/wiki/Pronunciation_assessment" 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