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href="https://et.wikipedia.org/wiki/Distributiivne_semantika" title="Distributiivne semantika – Estonian" lang="et" hreflang="et" data-title="Distributiivne semantika" data-language-autonym="Eesti" data-language-local-name="Estonian" class="interlanguage-link-target"><span>Eesti</span></a></li><li class="interlanguage-link interwiki-es mw-list-item"><a href="https://es.wikipedia.org/wiki/Sem%C3%A1ntica_distribucional" title="Semántica distribucional – Spanish" lang="es" hreflang="es" data-title="Semántica distribucional" data-language-autonym="Español" data-language-local-name="Spanish" class="interlanguage-link-target"><span>Español</span></a></li><li class="interlanguage-link interwiki-gl mw-list-item"><a href="https://gl.wikipedia.org/wiki/Sem%C3%A1ntica_distribucional" title="Semántica distribucional – Galician" lang="gl" hreflang="gl" data-title="Semántica distribucional" data-language-autonym="Galego" data-language-local-name="Galician" class="interlanguage-link-target"><span>Galego</span></a></li><li class="interlanguage-link interwiki-ko mw-list-item"><a href="https://ko.wikipedia.org/wiki/%EB%B6%84%ED%8F%AC_%EC%9D%98%EB%AF%B8%EB%A1%A0" title="분포 의미론 – Korean" lang="ko" hreflang="ko" data-title="분포 의미론" data-language-autonym="한국어" data-language-local-name="Korean" class="interlanguage-link-target"><span>한국어</span></a></li><li class="interlanguage-link interwiki-it mw-list-item"><a href="https://it.wikipedia.org/wiki/Semantica_distribuzionale" title="Semantica distribuzionale – Italian" lang="it" hreflang="it" data-title="Semantica distribuzionale" data-language-autonym="Italiano" data-language-local-name="Italian" class="interlanguage-link-target"><span>Italiano</span></a></li><li class="interlanguage-link interwiki-ru mw-list-item"><a href="https://ru.wikipedia.org/wiki/%D0%94%D0%B8%D1%81%D1%82%D1%80%D0%B8%D0%B1%D1%83%D1%82%D0%B8%D0%B2%D0%BD%D0%B0%D1%8F_%D1%81%D0%B5%D0%BC%D0%B0%D0%BD%D1%82%D0%B8%D0%BA%D0%B0" 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dir="ltr"><figure class="mw-default-size" typeof="mw:File/Thumb"><a href="/wiki/File:Distributional_semantics.png" class="mw-file-description"><img src="//upload.wikimedia.org/wikipedia/commons/thumb/c/ce/Distributional_semantics.png/220px-Distributional_semantics.png" decoding="async" width="220" height="156" class="mw-file-element" srcset="//upload.wikimedia.org/wikipedia/commons/thumb/c/ce/Distributional_semantics.png/330px-Distributional_semantics.png 1.5x, //upload.wikimedia.org/wikipedia/commons/thumb/c/ce/Distributional_semantics.png/440px-Distributional_semantics.png 2x" data-file-width="1468" data-file-height="1038" /></a><figcaption>How words are related in a given language is demonstrated in the "semantic space", which mathematically corresponds to the vector space.</figcaption></figure><div class="shortdescription nomobile noexcerpt noprint searchaux" style="display:none">Field of linguistics</div> <p><b>Distributional semantics</b><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> is a research area that develops and studies theories and methods for quantifying and categorizing semantic similarities between linguistic items based on their distributional properties in large samples of language data. The basic idea of distributional semantics can be summed up in the so-called <a href="/wiki/Distributionalism" title="Distributionalism">distributional</a> hypothesis: <i>linguistic items with similar distributions have similar meanings.</i> </p> <meta property="mw:PageProp/toc" /> <div class="mw-heading mw-heading2"><h2 id="Distributional_hypothesis">Distributional hypothesis</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Distributional_semantics&action=edit&section=1" title="Edit section: Distributional hypothesis"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>The <b>distributional hypothesis</b> in <a href="/wiki/Linguistics" title="Linguistics">linguistics</a> is derived from the <a href="/w/index.php?title=Semantic_theory&action=edit&redlink=1" class="new" title="Semantic theory (page does not exist)">semantic theory</a> of language usage, i.e. words that are used and occur in the same <a href="/wiki/Context_(language_use)" class="mw-redirect" title="Context (language use)">contexts</a> tend to purport similar meanings.<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> </p><p>The underlying idea that "a word is characterized by the company it keeps" was popularized by <a href="/wiki/J._R._Firth" class="mw-redirect" title="J. R. Firth">Firth</a> in the 1950s.<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><p>The distributional hypothesis is the basis for <a href="/wiki/Statistical_semantics" title="Statistical semantics">statistical semantics</a>. Although the Distributional Hypothesis originated in linguistics,<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><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> it is now receiving attention in <a href="/wiki/Cognitive_science" title="Cognitive science">cognitive science</a> especially regarding the context of word use.<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> </p><p>In recent years, the distributional hypothesis has provided the basis for the theory of <a href="/w/index.php?title=Similarity-based_generalization&action=edit&redlink=1" class="new" title="Similarity-based generalization (page does not exist)">similarity-based generalization</a> in language learning: the idea that children can figure out how to use words they've rarely encountered before by generalizing about their use from distributions of similar words.<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><sup id="cite_ref-8" class="reference"><a href="#cite_note-8"><span class="cite-bracket">[</span>8<span class="cite-bracket">]</span></a></sup> </p><p>The distributional hypothesis suggests that the more semantically similar two words are, the more distributionally similar they will be in turn, and thus the more that they will tend to occur in similar linguistic contexts. </p><p>Whether or not this suggestion holds has significant implications for both the <a href="/w/index.php?title=Data-sparsity&action=edit&redlink=1" class="new" title="Data-sparsity (page does not exist)">data-sparsity</a> problem in computational modeling,<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> and for the question of how children are able to learn language so rapidly given relatively impoverished input (this is also known as the problem of the <a href="/wiki/Poverty_of_the_stimulus" title="Poverty of the stimulus">poverty of the stimulus</a>). </p> <div class="mw-heading mw-heading2"><h2 id="Distributional_semantic_modeling_in_vector_spaces">Distributional semantic modeling in vector spaces</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Distributional_semantics&action=edit&section=2" title="Edit section: Distributional semantic modeling in vector spaces"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Distributional semantics favor the use of linear algebra as a computational tool and representational framework. The basic approach is to collect distributional information in high-dimensional vectors, and to define distributional/semantic similarity in terms of vector similarity.<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> Different kinds of similarities can be extracted depending on which type of distributional information is used to collect the vectors: <b>topical</b> similarities can be extracted by populating the vectors with information on which text regions the linguistic items occur in; <b>paradigmatic</b> similarities can be extracted by populating the vectors with information on which other linguistic items the items co-occur with. Note that the latter type of vectors can also be used to extract <b>syntagmatic</b> similarities by looking at the individual vector components. </p><p>The basic idea of a correlation between distributional and semantic similarity can be operationalized in many different ways. There is a rich variety of computational models implementing distributional semantics, including <a href="/wiki/Latent_semantic_analysis" title="Latent semantic analysis">latent semantic analysis</a> (LSA),<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><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> <a href="/wiki/Hyperspace_Analogue_to_Language" class="mw-redirect" title="Hyperspace Analogue to Language">Hyperspace Analogue to Language</a> (HAL), syntax- or dependency-based models,<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> <a href="/wiki/Random_indexing" title="Random indexing">random indexing</a>, <a href="/wiki/Semantic_folding" title="Semantic folding">semantic folding</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> and various variants of the <a href="/wiki/Topic_model" title="Topic model">topic model</a>.<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> </p><p>Distributional semantic models differ primarily with respect to the following parameters: </p> <ul><li>Context type (text regions vs. linguistic items)</li> <li>Context window (size, extension, etc.)</li> <li>Frequency weighting (e.g. <a href="/wiki/Entropy_(information_theory)" title="Entropy (information theory)">entropy</a>, <a href="/wiki/Pointwise_mutual_information" title="Pointwise mutual information">pointwise mutual information</a>,<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> etc.)</li> <li>Dimension reduction (e.g. <a href="/wiki/Random_indexing" title="Random indexing">random indexing</a>, <a href="/wiki/Singular_value_decomposition" title="Singular value decomposition">singular value decomposition</a>, etc.)</li> <li><a href="/wiki/Similarity_measure" title="Similarity measure">Similarity measure</a> (e.g. <a href="/wiki/Cosine_similarity" title="Cosine similarity">cosine similarity</a>, <a href="/wiki/Minkowski_distance" title="Minkowski distance">Minkowski distance</a>, etc.)</li></ul> <p>Distributional semantic models that use linguistic items as context have also been referred to as <b>word space, or vector space models</b>.<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><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> </p> <div class="mw-heading mw-heading2"><h2 id="Beyond_Lexical_Semantics">Beyond Lexical Semantics</h2><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Distributional_semantics&action=edit&section=3" title="Edit section: Beyond Lexical Semantics"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>While distributional semantics typically has been applied to lexical items—words and multi-word terms—with considerable success, not least due to its applicability as an input layer for neurally inspired deep learning models, <a href="/wiki/Lexical_semantics" title="Lexical semantics">lexical semantics</a>, i.e. the meaning of words, will only carry part of the semantics of an entire utterance. The meaning of a clause, e.g. <i>"Tigers love rabbits."</i>, can only partially be understood from examining the meaning of the three lexical items it consists of. Distributional semantics can straightforwardly be extended to cover larger linguistic item such as constructions, with and without non-instantiated items, but some of the base assumptions of the model need to be adjusted somewhat. <a href="/wiki/Construction_grammar" title="Construction grammar">Construction grammar</a> and its formulation of the lexical-syntactic continuum offers one approach for including more elaborate constructions in a distributional semantic model and some experiments have been implemented using the Random Indexing approach.<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> </p><p><a href="/w/index.php?title=Compositional_distributional_semantics&action=edit&redlink=1" class="new" title="Compositional distributional semantics (page does not exist)">Compositional distributional semantic</a> models extend distributional semantic models by explicit semantic functions that use syntactically based rules to combine the semantics of participating lexical units into a <i>compositional model</i> to characterize the semantics of entire phrases or sentences. This work was originally proposed by Stephen Clark, <a href="/wiki/Bob_Coecke" title="Bob Coecke">Bob Coecke</a>, and <a href="/wiki/Mehrnoosh_Sadrzadeh" title="Mehrnoosh Sadrzadeh">Mehrnoosh Sadrzadeh</a> of <a href="/wiki/University_of_Oxford" title="University of Oxford">Oxford University</a> in their 2008 paper, "A Compositional Distributional Model of Meaning".<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> Different approaches to composition have been explored—including neural models—and are under discussion at established workshops such as <a href="/wiki/SemEval" title="SemEval">SemEval</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> </p> <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=Distributional_semantics&action=edit&section=4" title="Edit section: Applications"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <p>Distributional semantic models have been applied successfully to the following tasks: </p> <ul><li>finding <a href="/wiki/Semantic_similarity" title="Semantic similarity">semantic similarity</a> between words and multi-word expressions;</li> <li><a href="/wiki/Keyword_clustering" title="Keyword clustering">word clustering</a> based on semantic similarity;</li> <li>automatic creation of <a href="/wiki/Thesauri" class="mw-redirect" title="Thesauri">thesauri</a> and bilingual dictionaries;</li> <li><a href="/wiki/Word_sense_disambiguation" class="mw-redirect" title="Word sense disambiguation">word sense disambiguation</a>;</li> <li>expanding search requests using synonyms and associations;</li> <li>defining the topic of a document;</li> <li><a href="/wiki/Document_clustering" title="Document clustering">document clustering</a> for <a href="/wiki/Information_retrieval" title="Information retrieval">information retrieval</a>;</li> <li><a href="/wiki/Data_mining" title="Data mining">data mining</a> and <a href="/wiki/Named_entities_recognition" class="mw-redirect" title="Named entities recognition">named entities recognition</a>;</li> <li>creating <a href="/wiki/Semantic_mapping_(literacy)" title="Semantic mapping (literacy)">semantic maps</a> of different subject domains;</li> <li><a href="/wiki/Paraphrasing_(computational_linguistics)" title="Paraphrasing (computational linguistics)">paraphrasing</a>;</li> <li><a href="/wiki/Sentiment_analysis" title="Sentiment analysis">sentiment analysis</a>;</li> <li>modeling selectional preferences of words.</li></ul> <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=Distributional_semantics&action=edit&section=5" title="Edit section: Software"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a rel="nofollow" class="external text" href="https://github.com/fozziethebeat/S-Space/">S-Space</a></li> <li><a rel="nofollow" class="external text" href="https://github.com/semanticvectors/semanticvectors/">SemanticVectors</a></li> <li><a rel="nofollow" class="external text" href="http://radimrehurek.com/gensim/index.html">Gensim</a></li> <li><a rel="nofollow" class="external text" href="http://www.linguatools.de/disco/disco-builder.html">DISCO Builder</a></li> <li><a rel="nofollow" class="external text" href="https://github.com/Lambda-3/Indra">Indra</a></li></ul> <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=Distributional_semantics&action=edit&section=6" title="Edit section: See also"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Conceptual_space" title="Conceptual space">Conceptual space</a></li> <li><a href="/wiki/Co-occurrence" title="Co-occurrence">Co-occurrence</a></li> <li><a href="/wiki/Distributional%E2%80%93relational_database" title="Distributional–relational database">Distributional–relational database</a></li> <li><a href="/wiki/Gensim" title="Gensim">Gensim</a></li> <li><a href="/wiki/Phraseme" title="Phraseme">Phraseme</a></li> <li><a href="/wiki/Random_indexing" title="Random indexing">Random indexing</a></li> <li><a href="/wiki/Sentence_embedding" title="Sentence embedding">Sentence embedding</a></li> <li><a href="/wiki/Statistical_semantics" title="Statistical semantics">Statistical semantics</a></li> <li><a href="/wiki/Word2vec" title="Word2vec">Word2vec</a></li> <li><a href="/wiki/Word_embedding" title="Word embedding">Word embedding</a></li></ul> <div class="mw-heading mw-heading3"><h3 id="People">People</h3><span class="mw-editsection"><span class="mw-editsection-bracket">[</span><a href="/w/index.php?title=Distributional_semantics&action=edit&section=7" title="Edit section: People"><span>edit</span></a><span class="mw-editsection-bracket">]</span></span></div> <ul><li><a href="/wiki/Scott_Deerwester" title="Scott Deerwester">Scott Deerwester</a></li> <li><a href="/wiki/Susan_Dumais" title="Susan Dumais">Susan Dumais</a></li> <li><a href="/wiki/J._R._Firth" class="mw-redirect" title="J. R. Firth">J. R. Firth</a></li> <li><a href="/wiki/George_Furnas" title="George Furnas">George Furnas</a></li> <li><a href="/wiki/Zellig_Harris" title="Zellig Harris">Zellig Harris</a></li> <li><a href="/wiki/Thomas_Landauer" title="Thomas Landauer">Thomas Landauer</a></li> <li><a href="/wiki/Magnus_Sahlgren" title="Magnus Sahlgren">Magnus Sahlgren</a></li></ul> <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=Distributional_semantics&action=edit&section=8" title="Edit section: References"><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 id="CITEREFLenciSahlgren2023" class="citation book cs1">Lenci, Alessandro; Sahlgren, Magnus (2023). <i>Distributional Semantics</i>. 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processing">Text processing</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Text_mining" title="Text mining">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 href="/wiki/Text_mining" title="Text mining">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_segmentation21" 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 class="mw-selflink selflink">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" title="Pronunciation assessment">Pronunciation assessment</a></li> <li><a href="/wiki/Spell_checker" title="Spell checker">Spell checker</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%"><a href="/wiki/Natural-language_user_interface" title="Natural-language user interface">Natural language<br />user interface</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/Chatbot" title="Chatbot">Chatbot</a></li> <li><a href="/wiki/Interactive_fiction" title="Interactive fiction">Interactive fiction</a> (c.f. <a href="/wiki/Syntax_guessing" class="mw-redirect" title="Syntax guessing">Syntax guessing</a>)</li> <li><a href="/wiki/Question_answering" title="Question answering">Question answering</a></li> <li><a href="/wiki/Virtual_assistant" title="Virtual assistant">Virtual assistant</a></li> <li><a href="/wiki/Voice_user_interface" title="Voice user interface">Voice user interface</a></li></ul> </div></td></tr><tr><th scope="row" class="navbox-group" style="width:1%">Related</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/Formal_semantics_(natural_language)" title="Formal semantics (natural language)">Formal semantics</a></li> <li><a href="/wiki/Hallucination_(artificial_intelligence)" title="Hallucination (artificial intelligence)">Hallucination</a></li> <li><a href="/wiki/Natural_Language_Toolkit" title="Natural Language Toolkit">Natural Language Toolkit</a></li> <li><a href="/wiki/SpaCy" title="SpaCy">spaCy</a></li></ul> </div></td></tr></tbody></table></div>    </div><noscript><img src="https://login.wikimedia.org/wiki/Special:CentralAutoLogin/start?useformat=desktop&type=1x1&usesul3=0" alt="" width="1" height="1" style="border: none; position: absolute;"></noscript> <div class="printfooter" data-nosnippet="">Retrieved from "<a dir="ltr" href="https://en.wikipedia.org/w/index.php?title=Distributional_semantics&oldid=1268345775">https://en.wikipedia.org/w/index.php?title=Distributional_semantics&oldid=1268345775</a>"</div></div> <div id="catlinks" class="catlinks" data-mw="interface"><div id="mw-normal-catlinks" class="mw-normal-catlinks"><a href="/wiki/Help:Category" 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