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(PDF) Corpus-Based Stemming Using Co-occurrence Stats
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window.loswp.shouldDetectTimezone = true; window.loswp.shouldShowBulkDownload = true; window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":2788024,"created_at":"2013-03-03T15:08:49.336-08:00","from_world_paper_id":null,"updated_at":"2025-02-02T23:06:59.329-08:00","_data":{"ai_title_tag":"Corpus-Based Stemming Using Co-occurrence Stats","grobid_abstract":"Stemming is used in many information retrieval (IR) systems to reduce variant word forms to common roots. It is one of the simplest applications of natural language processing to IR, and one of the most e ective in terms of user acceptance and consistent, though small, retrieval improvements. Current stemming techniques do not, however, re ect the language use in speci c corpora and this can lead to occasional serious retrieval failures. We propose a technique for using corpus-based word variant co-occurrence statistics to modify or create a stemmer. The experimental results generated using English newspaper and legal text and Spanish text demonstrate the viability of this technique and its advantages relative to conventional approaches.","grobid_abstract_attachment_id":"30740561"},"document_type":"paper","pre_hit_view_count_baseline":0,"quality":"high","language":"en","title":"Corpus-Based Stemming using Co-occurrence of Word","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [1389]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "full_page_mobile_sutd_modal"; window.loswp.useOptimizedScribd4genScript = false; window.loginModal = {}; window.loginModal.appleClientId = 'edu.academia.applesignon'; window.userInChina = "false";</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{"location":"swp-splash-paper-cover","attachmentId":30740561,"attachmentType":"pdf"}"><img alt="First page of “Corpus-Based Stemming using Co-occurrence of Word”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/30740561/mini_magick20190426-9171-1fxesgg.png?1556319627" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/images/single_work_splash/adobe_icon.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">Corpus-Based Stemming using Co-occurrence of Word</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="1389" href="https://umass.academia.edu/WBruceCroft"><img alt="Profile image of W. Bruce Croft" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/1389/573/687/s65_w._bruce.croft.jpg" />W. Bruce Croft</a></div><div class="ds-work-card--detail"><div class="ds-work-card--work-metadata"><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">visibility</span><p class="ds2-5-body-sm" id="work-metadata-view-count">…</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">description</span><p class="ds2-5-body-sm">28 pages</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">link</span><p class="ds2-5-body-sm">1 file</p></div></div><script>(async () => { const workId = 2788024; const worksViewsPath = "/v0/works/views?subdomain_param=api&work_ids%5B%5D=2788024"; const getWorkViews = async (workId) => { const response = await fetch(worksViewsPath); if (!response.ok) { throw new Error('Failed to load work views'); } const data = await response.json(); return data.views[workId]; }; // Get the view count for the work - we send this immediately rather than waiting for // the DOM to load, so it can be available as soon as possible (but without holding up // the backend or other resource requests, because it's a bit expensive and not critical). const viewCount = await getWorkViews(workId); const updateViewCount = (viewCount) => { try { const viewCountNumber = parseInt(viewCount, 10); if (viewCountNumber === 0) { // Remove the whole views element if there are zero views. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); return; } const commaizedViewCount = viewCountNumber.toLocaleString(); const viewCountBody = document.getElementById('work-metadata-view-count'); if (!viewCountBody) { throw new Error('Failed to find work views element'); } viewCountBody.textContent = `${commaizedViewCount} views`; } catch (error) { // Remove the whole views element if there was some issue parsing. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); throw new Error(`Failed to parse view count: ${viewCount}`, error); } }; // If the DOM is still loading, wait for it to be ready before updating the view count. if (document.readyState === "loading") { document.addEventListener('DOMContentLoaded', () => { updateViewCount(viewCount); }); // Otherwise, just update it immediately. } else { updateViewCount(viewCount); } })();</script></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">Stemming is used in many information retrieval (IR) systems to reduce variant word forms to common roots. It is one of the simplest applications of natural language processing to IR, and one of the most e ective in terms of user acceptance and consistent, though small, retrieval improvements. Current stemming techniques do not, however, re ect the language use in speci c corpora and this can lead to occasional serious retrieval failures. We propose a technique for using corpus-based word variant co-occurrence statistics to modify or create a stemmer. The experimental results generated using English newspaper and legal text and Spanish text demonstrate the viability of this technique and its advantages relative to conventional approaches.</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":30740561,"attachmentType":"pdf","workUrl":"https://www.academia.edu/2788024/Corpus_Based_Stemming_using_Co_occurrence_of_Word"}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--work-card","attachmentId":30740561,"attachmentType":"pdf","workUrl":"https://www.academia.edu/2788024/Corpus_Based_Stemming_using_Co_occurrence_of_Word"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div><div class="ds-signup-banner-trigger-container"><div class="ds-signup-banner-trigger ds-signup-banner-trigger-control"></div></div><div class="ds-signup-banner ds-signup-banner-control"><div id="ds-signup-banner-close-button"><button class="ds2-5-button ds2-5-button--secondary ds2-5-button--inverse"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">close</span></button></div><div class="ds-signup-banner-ctas"><img src="//a.academia-assets.com/images/academia-logo-capital-white.svg" /><h4 class="ds2-5-heading-serif-sm">Sign up for access to the world's latest research</h4><button class="ds2-5-button ds2-5-button--inverse ds2-5-button--full-width js-swp-download-button" data-signup-modal="{"location":"signup-banner"}">Sign up for free<span class="material-symbols-outlined" style="font-size: 20px" translate="no">arrow_forward</span></button></div><div class="ds-signup-banner-divider"></div><div class="ds-signup-banner-reasons"><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Get notified about relevant papers</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Save papers to use in your research</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Join the discussion with peers</span></div><div class="ds-signup-banner-reasons-item"><span class="material-symbols-outlined" style="font-size: 24px" translate="no">check</span><span>Track your impact</span></div></div></div><script>(() => { // Set up signup banner show/hide behavior: // 1. 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Bruce Croft</a></div><p class="ds-related-work--metadata ds2-5-body-xs">1994</p><p class="ds-related-work--abstract ds2-5-body-sm">Stemming is used in many information retrieval (IR) systems to reduce word forms to common roots. It is one of the simplest and most successful applications of natural language processing for IR. Current stemming algorithms are, however, either in exible or di cult to adapt to the speci c characteristics of a text corpus, except by the manual de nition of exception lists. We propose a technique for using corpus-based word co-occurrence statistics to modify a stemmer. Experiments show that this technique is e ective and is very suitable for query-based stemming.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Corpus-specific stemming using word form co-occurence","attachmentId":30740472,"attachmentType":"pdf","work_url":"https://www.academia.edu/2787943/Corpus_specific_stemming_using_word_form_co_occurence","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/2787943/Corpus_specific_stemming_using_word_form_co_occurence"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="3566591" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/3566591/Stemming_in_Spanish_A_First_Approach_to_its_Impact_on_Information_Retrieval">Stemming in Spanish: A First Approach to its Impact on Information Retrieval</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="4246465" href="https://usal.academia.edu/RaquelG%C3%B3mez">Raquel Gómez-Díaz</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Most models and techniques employed in Information Retireval at some time or other use frecuency counts of the terms appearing in both documents and queries. Many words that derive from the same stem have a close semantic content. Locating stems common to several words and grouping them by replacing them with the corresponding stem can improve the working of these systems. Stemming procedures differ, however, depending on the different languages. We describe a stemmer for Spanish and the tests carried out by applying it to Information Retrieval.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Stemming in Spanish: A First Approach to its Impact on Information Retrieval","attachmentId":31277274,"attachmentType":"pdf","work_url":"https://www.academia.edu/3566591/Stemming_in_Spanish_A_First_Approach_to_its_Impact_on_Information_Retrieval","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/3566591/Stemming_in_Spanish_A_First_Approach_to_its_Impact_on_Information_Retrieval"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="15204532" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/15204532/University_of_Padua_at_CLEF_2002_Experiments_to_evaluate_a_statistical_stemming_algorithm">University of Padua at CLEF 2002: Experiments to evaluate a statistical stemming algorithm</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="34260639" href="https://unipd.academia.edu/NicolaFerro">Nicola Ferro</a></div><p class="ds-related-work--abstract ds2-5-body-sm">In Information Retrieval (IR), stemming is used to reduce variant word forms to common root. The assumption is that if two words have the same root, then they represent the same concept. Hence stemming permits a IR system to match query and document terms which are related to a same meaning but which can appear in different morphological variants. In this paper we will report our participation in CLEF 2002 Italian monolingual task, whose aim was to evaluate a statistical stemming algorithm based on link analysis. Considering that a word is formed by a prefix (stem) and a suffix, the key idea is that the interlinked prefixes and suffixes form a community of substrings. Hence discovering these communities means searching for the best word splits which give the best word stems. The results show that stemming improves the IR effectiveness. They also show that effectiveness level of our algorithm, which does not incorporate any heuristics nor linguistic knowledge, is comparable to that of an algorithm based on a-priori linguistic knowledge. This is an encouraging result, particularly in a multi-lingual context.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"University of Padua at CLEF 2002: Experiments to evaluate a statistical stemming algorithm","attachmentId":43436743,"attachmentType":"pdf","work_url":"https://www.academia.edu/15204532/University_of_Padua_at_CLEF_2002_Experiments_to_evaluate_a_statistical_stemming_algorithm","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/15204532/University_of_Padua_at_CLEF_2002_Experiments_to_evaluate_a_statistical_stemming_algorithm"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="28353309" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/28353309/A_NEW_STEMMER_TO_IMPROVE_INFORMATION_RETRIEVAL">A NEW STEMMER TO IMPROVE INFORMATION RETRIEVAL</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="48972519" href="https://isgs.academia.edu/WahibaBenAbdessalemKar%C3%A2a">Wahiba Ben Abdessalem Karâa</a></div><p class="ds-related-work--abstract ds2-5-body-sm">A stemming is a technique used to reduce words to their root form, by removing derivational and inflectional affixes. The stemming is widely used in information retrieval tasks. Many researchers demonstrate that stemming improves the performance of information retrieval systems. Porter stemmer is the most common algorithm for English stemming. However, this stemming algorithm has several drawbacks, since its simple rules cannot fully describe English morphology. Errors made by this stemmer may affect the information retrieval performance. The present paper proposes an improved version of the original Porter stemming algorithm for the English language. The proposed stemmer is evaluated using the error counting method. With this method, the performance of a stemmer is computed by calculating the number of understemming and overstemming errors. The obtained results show an improvement in stemming accuracy, compared with the original stemmer, but also compared to other stemmers such as Paice and Lovins stemmers. We prove, in addition, that the new version of porter stemmer affects the information retrieval performance.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A NEW STEMMER TO IMPROVE INFORMATION RETRIEVAL","attachmentId":48686363,"attachmentType":"pdf","work_url":"https://www.academia.edu/28353309/A_NEW_STEMMER_TO_IMPROVE_INFORMATION_RETRIEVAL","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/28353309/A_NEW_STEMMER_TO_IMPROVE_INFORMATION_RETRIEVAL"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="89174137" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/89174137/A_systematic_review_of_text_stemming_techniques">A systematic review of text stemming techniques</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="16379301" href="https://pu.academia.edu/JasmeetSingh">Jasmeet Singh</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Artificial Intelligence Review, 2016</p><p class="ds-related-work--abstract ds2-5-body-sm">Stemming is a program that matches the morphological variants of the word to its root word. Stemming is extensively used as a pre-processing tool in the field of natural language processing, information retrieval, and language modeling. Though a lot of advancements have been made in the field, yet organized arrangement of the previous work and efforts are lacking in this field. In this paper, we present a review of the text stemming theory, algorithms, and applications. It first describes the existing literature relevant to text stemming by classifying it according to certain key parameters; then it describes the deep analysis of some well-known stemming algorithms on standard data sets. In the end, the current state-of-theart and certain open issues related to unsupervised stemming are presented. The main aim of this paper is to provide an extensive and useful understanding of the important aspects of text stemming. The open issues and analysis of the current stemming techniques will help the researchers to think of new lines to conduct research in future.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A systematic review of text stemming techniques","attachmentId":93021601,"attachmentType":"pdf","work_url":"https://www.academia.edu/89174137/A_systematic_review_of_text_stemming_techniques","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/89174137/A_systematic_review_of_text_stemming_techniques"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="63268543" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/63268543/A_survey_of_stemming_algorithms_in_information_retrieval">A survey of stemming algorithms in information retrieval</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="2685140" href="https://upm-es.academia.edu/Ang%C3%A9licaDeAntonio">Angélica de Antonio</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Information Research</p><p class="ds-related-work--abstract ds2-5-body-sm">Background. During the last fifty years, improved information retrieval techniques have become necessary because of the huge amount of information people have available, which continues to increase rapidly due to the use of new technologies and the Internet. Stemming is one of the processes that can improve information retrieval in terms of accuracy and performance. Aim. This paper provides a detailed assessment of the current status of the stemming process framed in an information retrieval application field by tracing its historical evolution. Method. Papers presenting the first approaches for stemming were reviewed to extract their main features, benefits and drawbacks. Additionally, papers dealing with stemmers for non-English languages or with some more recent proposals were also consulted and compiled. Finally, experimental papers defining the most well-known methods and metrics aimed at evaluating and classifying stemmers were also taken into account to expose their contribut...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A survey of stemming algorithms in information retrieval","attachmentId":75752097,"attachmentType":"pdf","work_url":"https://www.academia.edu/63268543/A_survey_of_stemming_algorithms_in_information_retrieval","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/63268543/A_survey_of_stemming_algorithms_in_information_retrieval"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="118815502" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/118815502/Effective_and_Robust_Query_Based_Stemming">Effective and Robust Query-Based Stemming</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="25722510" href="https://independent.academia.edu/SwapanKumarParui">Swapan Kumar Parui</a></div><p class="ds-related-work--metadata ds2-5-body-xs">ACM Transactions on Information Systems, 2013</p><p class="ds-related-work--abstract ds2-5-body-sm">Stemming is a widely used technique in information retrieval systems to address the vocabulary mismatch problem arising out of morphological phenomena. The major shortcoming of the commonly used stemmers is that they accept the morphological variants of the query words without considering their thematic coherence with the given query, which leads to poor performance. Moreover, for many queries, such approaches also produce retrieval performance that is poorer than no stemming, thereby degrading the robustness. The main goal of this article is to present corpus-based fully automatic stemming algorithms which address these issues. A set of experiments on six TREC collections and three other non-English collections containing news and web documents shows that the proposed query-based stemming algorithms consistently and significantly outperform four state of the art strong stemmers of completely varying principles. Our experiments also confirm that the robustness of the proposed query-...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Effective and Robust Query-Based Stemming","attachmentId":114351022,"attachmentType":"pdf","work_url":"https://www.academia.edu/118815502/Effective_and_Robust_Query_Based_Stemming","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/118815502/Effective_and_Robust_Query_Based_Stemming"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="3566589" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/3566589/Stemming_and_n_grams_in_Spanish_an_evaluation_of_their_impact_on_information_retrieval">Stemming and n-grams in Spanish: an evaluation of their impact on information retrieval</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="4246465" href="https://usal.academia.edu/RaquelG%C3%B3mez">Raquel Gómez-Díaz</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Information Science, 2000</p><p class="ds-related-work--abstract ds2-5-body-sm">At some stage, most of the models and techniques implemented in IR use frequency counts of the terms appearing in documents and in queries.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Stemming and n-grams in Spanish: an evaluation of their impact on information retrieval","attachmentId":50226905,"attachmentType":"pdf","work_url":"https://www.academia.edu/3566589/Stemming_and_n_grams_in_Spanish_an_evaluation_of_their_impact_on_information_retrieval","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/3566589/Stemming_and_n_grams_in_Spanish_an_evaluation_of_their_impact_on_information_retrieval"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="19538311" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/19538311/A_new_stemmer_to_improve_information_retreival">A new stemmer to improve information retreival</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="39858147" href="https://isg-tn.academia.edu/WahibaBenAbdessalem">Wahiba Ben Abdessalem</a></div><p class="ds-related-work--abstract ds2-5-body-sm">A stemming is a technique used to reduce words to their root form, by removing derivational and inflectional affixes. The stemming is widely used in information retrieval tasks. Many researchers demonstrate that stemming improves the performance of information retrieval systems. Porter stemmer is the most common algorithm for English stemming. However, this stemming algorithm has several drawbacks, since its simple rules cannot fully describe English morphology. Errors made by this stemmer may affect the information retrieval performance.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"A new stemmer to improve information retreival","attachmentId":40682439,"attachmentType":"pdf","work_url":"https://www.academia.edu/19538311/A_new_stemmer_to_improve_information_retreival","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/19538311/A_new_stemmer_to_improve_information_retreival"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="17129913" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/17129913/Automatic_Language_Specific_Stemming_in_Information_Retrieval">Automatic Language-Specific Stemming in Information Retrieval</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="60660" href="https://chicago.academia.edu/JohnGoldsmith">John Goldsmith</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Lecture Notes in Computer Science, 2001</p><p class="ds-related-work--abstract ds2-5-body-sm">We employ Automorphology, an MDL-based algorithm that determines the suffixes present in a language-sample with no prior knowledge of the language in question, and describe our experiments on the usefulness of this approach for Information Retrieval, employing this stemmer in a SMARTbased IR engine.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Automatic Language-Specific Stemming in Information Retrieval","attachmentId":39347791,"attachmentType":"pdf","work_url":"https://www.academia.edu/17129913/Automatic_Language_Specific_Stemming_in_Information_Retrieval","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/17129913/Automatic_Language_Specific_Stemming_in_Information_Retrieval"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--sticky-ctas","attachmentId":30740561,"attachmentType":"pdf","workUrl":null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{"location":"download-pdf-button--sticky-ctas","attachmentId":30740561,"attachmentType":"pdf","workUrl":null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_30740561" style="display: none"><div class="scribd--being-converted-container">This document is currently being converted. 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href="https://independent.academia.edu/NureniAzeez" rel="nofollow">Nureni Azeez</a></div><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Context-Aware Stemming Algorithm for Semantically Related Root Words","attachmentId":43230703,"attachmentType":"pdf","work_url":"https://www.academia.edu/22635406/Context_Aware_Stemming_Algorithm_for_Semantically_Related_Root_Words","alternativeTracking":true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-related-work-grid-card-view-pdf" href="https://www.academia.edu/22635406/Context_Aware_Stemming_Algorithm_for_Semantically_Related_Root_Words"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" 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