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window.loswp.translateUrl = "https://www.academia.edu/login?post_login_redirect_url=https%3A%2F%2Fwww.academia.edu%2F101689417%2FLearning_phrase_based_spelling_error_models_from_clickthrough_data%3Fshow_translation%3Dtrue"; window.loswp.previewableAttachments = [{"id":102160936,"identifier":"Attachment_102160936","shouldShowBulkDownload":false}]; window.loswp.shouldDetectTimezone = true; window.loswp.shouldShowBulkDownload = true; window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":101689417,"created_at":"2023-05-12T17:20:37.142-07:00","from_world_paper_id":233597269,"updated_at":"2024-11-23T14:02:34.087-08:00","_data":{"grobid_abstract":"This paper explores the use of clickthrough data for query spelling correction. First, large amounts of query-correction pairs are derived by analyzing users' query reformulation behavior encoded in the clickthrough data. Then, a phrase-based error model that accounts for the transformation probability between multi-term phrases is trained and integrated into a query speller system. Experiments are carried out on a human-labeled data set. Results show that the system using the phrase-based error model outperforms significantly its baseline systems. 3 Clickthrough Data and Spelling Correction This section describes the way the query-correction pairs are extracted from click","publication_date":"2010,,","grobid_abstract_attachment_id":"102160936"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Learning phrase-based spelling error models from clickthrough data","broadcastable":false,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [269471175]; 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.loswp.appleClientId = 'edu.academia.applesignon';</script><script defer="" 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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">Learning phrase-based spelling error models from clickthrough data</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="269471175" href="https://independent.academia.edu/MicolDaniel"><img alt="Profile image of Daniel Micol" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/269471175/120030388/109353029/s65_daniel.micol.png" />Daniel Micol</a></div><p class="ds-work-card--detail ds2-5-body-sm">2010</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" 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data-login_uri="https://www.academia.edu/registrations/google_one_tap" data-moment_callback="onGoogleOneTapEvent" id="g_id_onload"></div><div class="ds-top-related-works--grid-container"><div class="ds-related-content--container ds-top-related-works--container"><h2 class="ds-related-content--heading">Related papers</h2><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="0" data-entity-id="6725503" 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/6725503/Learning_a_Spelling_Error_Model_from_Search_Query_Logs">Learning a Spelling Error Model from Search Query Logs</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="11028268" href="https://independent.academia.edu/FarooqAhmad18">Farooq Ahmad</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2005</p><div 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href="https://www.academia.edu/59965783/Exploring_distributional_similarity_based_models_for_query_spelling_correction">Exploring distributional similarity based models for query spelling correction</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="9328515" href="https://independent.academia.edu/MuhuaZhu">Muhua Zhu</a></div><p class="ds-related-work--metadata ds2-5-body-xs">… and the 44th annual meeting of the …, 2006</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":"Exploring distributional similarity based models for query spelling correction","attachmentId":73622956,"attachmentType":"pdf","work_url":"https://www.academia.edu/59965783/Exploring_distributional_similarity_based_models_for_query_spelling_correction","alternativeTracking":true}"><span 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class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="9944263" href="https://independent.academia.edu/MadhuraPande">Madhura Pande</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 5: Industry Track)</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":"Search Query Spell Correction with Weak Supervision in E-commerce","attachmentId":113188679,"attachmentType":"pdf","work_url":"https://www.academia.edu/117293747/Search_Query_Spell_Correction_with_Weak_Supervision_in_E_commerce","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/117293747/Search_Query_Spell_Correction_with_Weak_Supervision_in_E_commerce"><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="6426942" 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/6426942/Spelling_Correction_as_an_Iterative_Process_that_Exploits_the_Collective_Knowledge_of_Web_Users">Spelling Correction as an Iterative Process that Exploits the Collective Knowledge of Web Users</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="10129560" href="https://tudelft.academia.edu/ionsilviu">ion silviu</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2004</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":"Spelling Correction as an Iterative Process that Exploits the Collective Knowledge of Web Users","attachmentId":33228639,"attachmentType":"pdf","work_url":"https://www.academia.edu/6426942/Spelling_Correction_as_an_Iterative_Process_that_Exploits_the_Collective_Knowledge_of_Web_Users","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/6426942/Spelling_Correction_as_an_Iterative_Process_that_Exploits_the_Collective_Knowledge_of_Web_Users"><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="2661513" 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/2661513/A_Discriminative_Model_for_Query_Spelling_Correction_with_Latent_Structural_SVM">A Discriminative Model for Query Spelling Correction with Latent Structural SVM</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="9644" href="https://illinois.academia.edu/DRoth">Dan Roth</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Abstract Discriminative training in query spelling correction is difficult due to the complex internal structures of the data. Recent work on query spelling correction suggests a two stage approach a noisy channel model that is used to retrieve a number of candidate corrections, followed by discriminatively trained ranker applied to these candidates. The ranker, however, suffers from the fact the low recall of the first, suboptimal, search stage.</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 Discriminative Model for Query Spelling Correction with Latent Structural SVM","attachmentId":30660895,"attachmentType":"pdf","work_url":"https://www.academia.edu/2661513/A_Discriminative_Model_for_Query_Spelling_Correction_with_Latent_Structural_SVM","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/2661513/A_Discriminative_Model_for_Query_Spelling_Correction_with_Latent_Structural_SVM"><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="2597331" 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/2597331/Spelling_correction_for_search_engine_queries">Spelling correction for search engine queries</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="390632" href="https://lisboa.academia.edu/BrunoMartins">Bruno Martins</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2004</p><p class="ds-related-work--abstract ds2-5-body-sm">Search engines have become the primary means of accessing information on the Web. However, recent studies show misspelled words are very common in queries to these systems. When users misspell query, the results are incorrect or provide inconclusive information. In this work, we discuss the integration of a spelling correction component into tumba!, our community Web search 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":"Spelling correction for search engine queries","attachmentId":30610311,"attachmentType":"pdf","work_url":"https://www.academia.edu/2597331/Spelling_correction_for_search_engine_queries","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/2597331/Spelling_correction_for_search_engine_queries"><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="2687054" 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/2687054/An_In_depth_Study_of_the_Automatic_Detection_and_Correction_of_Spelling_Mistakes">An In-depth Study of the Automatic Detection and Correction of Spelling Mistakes</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="35462" href="https://glasgow.academia.edu/IadhOunis">Iadh Ounis</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2005</p><p class="ds-related-work--abstract ds2-5-body-sm">ABSTRACT This paper discusses the issues involved in an information retrieval system when spelling errors are encountered in a query. We look at two classical algorithms that may be used to correct these errors and their consequent effect on the system's performance. The algorithms are the Levenshtein Distance and the Longest Common Subsequence. We experiment on a variety of test data and explore the impact of certain errors on an information retrieval system.</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":"An In-depth Study of the Automatic Detection and Correction of Spelling Mistakes","attachmentId":30680850,"attachmentType":"pdf","work_url":"https://www.academia.edu/2687054/An_In_depth_Study_of_the_Automatic_Detection_and_Correction_of_Spelling_Mistakes","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/2687054/An_In_depth_Study_of_the_Automatic_Detection_and_Correction_of_Spelling_Mistakes"><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="30197878" 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/30197878/Toward_filling_the_gap_between_interactive_and_fully_automatic_spelling_correction_using_the_linguistic_context">Toward filling the gap between interactive and fully-automatic spelling correction using the linguistic context</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="32541866" href="https://independent.academia.edu/PRuch">Patrick Ruch</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2001</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":"Toward filling the gap between interactive and fully-automatic spelling correction using the linguistic context","attachmentId":50656872,"attachmentType":"pdf","work_url":"https://www.academia.edu/30197878/Toward_filling_the_gap_between_interactive_and_fully_automatic_spelling_correction_using_the_linguistic_context","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/30197878/Toward_filling_the_gap_between_interactive_and_fully_automatic_spelling_correction_using_the_linguistic_context"><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="92846021" 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/92846021/Automatic_spelling_error_detection_and_correction_for_Tigrigna_information_retrieval_a_hybrid_approach">Automatic spelling error detection and correction for Tigrigna information retrieval: a hybrid approach</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="45054934" href="https://independent.academia.edu/GebremariamSolomon">Solomon D Gebremariam</a><span>, </span><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="171721299" href="https://independent.academia.edu/beeiiaes">beei iaes</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Bulletin of Electrical Engineering and Informatics, 2023</p><p class="ds-related-work--abstract ds2-5-body-sm">This paper proposes a hybrid approach to design and implement query spelling error detection and correction (SEDC) for Tigrigna information retrieval (IR). Our approach, which is the main contribution to this work, is fast and robust to achieve better performance and also helps the users to easily insert their corrected queries to retrieve relevant information from the IR. This is achieved by combining the normalized measure of bigram overlap using the Jaccard coefficient (J.C) technique, a dynamic programming algorithm for edit distance, and probability of occurrence, which were used to make suggestions for the misspelt words. Our approach was evaluated on the SEDC subtasks separately. It achieved an F-measure of 98.85% on the spelling error detection subtask and an accuracy of 95.36% on the spelling error correction subtask. Thus, a comparison was conducted between our approach and the existing Tigrigna spell checker. It is found that our approach outperformed the existing spell checker and shows a 5.36% improvement in accuracy. This is by far the most promising result with regard to correcting the misspelt users' queries and improving the overall performance of the IR.</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 spelling error detection and correction for Tigrigna information retrieval: a hybrid approach","attachmentId":95746649,"attachmentType":"pdf","work_url":"https://www.academia.edu/92846021/Automatic_spelling_error_detection_and_correction_for_Tigrigna_information_retrieval_a_hybrid_approach","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/92846021/Automatic_spelling_error_detection_and_correction_for_Tigrigna_information_retrieval_a_hybrid_approach"><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":102160936,"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":102160936,"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_102160936" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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