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"https://www.academia.edu/login?post_login_redirect_url=https%3A%2F%2Fwww.academia.edu%2F2687054%2FAn_In_depth_Study_of_the_Automatic_Detection_and_Correction_of_Spelling_Mistakes%3Fauto%3Ddownload"; window.loswp.translateUrl = "https://www.academia.edu/login?post_login_redirect_url=https%3A%2F%2Fwww.academia.edu%2F2687054%2FAn_In_depth_Study_of_the_Automatic_Detection_and_Correction_of_Spelling_Mistakes%3Fshow_translation%3Dtrue"; window.loswp.previewableAttachments = [{"id":30680850,"identifier":"Attachment_30680850","shouldShowBulkDownload":false}]; window.loswp.shouldDetectTimezone = true; window.loswp.shouldShowBulkDownload = true; window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":2687054,"created_at":"2013-02-26T14:53:36.209-08:00","from_world_paper_id":null,"updated_at":"2021-01-12T04:10:59.876-08:00","_data":{"abstract":"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.","journal_name":"Information Retrieval Workshop","publication_date":"2005,1,10"},"document_type":"paper","pre_hit_view_count_baseline":0,"quality":"high","language":"en","title":"An In-depth Study of the Automatic Detection and Correction of Spelling Mistakes","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [35462]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "control"; window.loswp.useOptimizedScribd4genScript = false; window.loswp.appleClientId = 'edu.academia.applesignon';</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":30680850,"attachmentType":"pdf"}"><img alt="First page of “An In-depth Study of the Automatic Detection and Correction of Spelling Mistakes”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/30680850/mini_magick20180818-9793-149lytr.png?1534585025" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/assets/single_work_splash/adobe.icon-574afd46eb6b03a77a153a647fb47e30546f9215c0ee6a25df597a779717f9ef.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">An In-depth Study of the Automatic Detection and Correction of Spelling Mistakes</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="35462" href="https://glasgow.academia.edu/IadhOunis"><img alt="Profile image of Iadh Ounis" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/35462/82158/90024/s65_iadh.ounis.jpg" />Iadh Ounis</a></div><p class="ds-work-card--detail ds2-5-body-sm">2005</p><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">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-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{"location":"continue-reading-button--work-card","attachmentId":30680850,"attachmentType":"pdf","workUrl":"https://www.academia.edu/2687054/An_In_depth_Study_of_the_Automatic_Detection_and_Correction_of_Spelling_Mistakes"}">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":30680850,"attachmentType":"pdf","workUrl":"https://www.academia.edu/2687054/An_In_depth_Study_of_the_Automatic_Detection_and_Correction_of_Spelling_Mistakes"}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div></div><div data-auto_select="false" data-client_id="331998490334-rsn3chp12mbkiqhl6e7lu2q0mlbu0f1b" data-doc_id="30680850" data-landing_url="https://www.academia.edu/2687054/An_In_depth_Study_of_the_Automatic_Detection_and_Correction_of_Spelling_Mistakes" 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="75300300" 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/75300300/Spell_checking_queries_by_combining_Levenshtein_and_Stoilos_distances">Spell-checking queries by combining Levenshtein and Stoilos distances</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="87469612" href="https://independent.academia.edu/LinaSoualmia">Lina Soualmia</a></div><p class="ds-related-work--abstract ds2-5-body-sm">We propose in this paper a simple yet efficient method in order to correct misspellings of queries submitted by users to an online search tool in medicine. In addition to exact phonetic term matching, we test two approximate string comparators: the string distance metric of Stoilos and the Levenshtein edit distance. We propose here to combine them. At a threshold comparator score of 0.2, the normalized Levenshtein algorithm gives the highest recall of 76% but the highest precision 94% is obtained by combining the two distances of Levenshtein and Stoilos. Despite the well-known good performance of the normalized edit distance of Levenshtein, we show in this paper that its combination with the Stoilos algorithm improves the results for misspelling correction of user queries. This method may be applied to text documents in Electronic Health Records or clinical documents.</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":"Spell-checking queries by combining Levenshtein and Stoilos distances","attachmentId":83123986,"attachmentType":"pdf","work_url":"https://www.academia.edu/75300300/Spell_checking_queries_by_combining_Levenshtein_and_Stoilos_distances","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/75300300/Spell_checking_queries_by_combining_Levenshtein_and_Stoilos_distances"><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="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 class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="451350" 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/451350/Implementation_Aspects_and_Applications_of_a_Spelling_Correction_Algorithm">Implementation Aspects and Applications of a Spelling Correction 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="339543" href="https://kth.academia.edu/ViggoKann">Viggo Kann</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Text as a Linguistic …, 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":"Implementation Aspects and Applications of a Spelling Correction Algorithm","attachmentId":3484770,"attachmentType":"pdf","work_url":"https://www.academia.edu/451350/Implementation_Aspects_and_Applications_of_a_Spelling_Correction_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/451350/Implementation_Aspects_and_Applications_of_a_Spelling_Correction_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="78804300" 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/78804300/Design_and_Analysis_of_Algorithm_to_Search_Documents_with_Misspelled_Input">Design and Analysis of Algorithm to Search Documents with Misspelled Input</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="9283484" href="https://independent.academia.edu/ShrabantiMandal">Shrabanti Mandal</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2013</p><p class="ds-related-work--abstract ds2-5-body-sm">Clustering is the useful technique for discovering of data distribution and patterns in the underlying data. The goal of clustering is to discover both the dense and the sparse regions in a data set. The main emphasis has been to cluster with high accuracy as possible and search the required data from them, while keeping the input/output (I/O) cost high. Thus, it is necessary to investigate the principle of clustering and searching to design efficient algorithms which meet the specific requirement of minimizing the I/O operation. So our objective is to build a searching tool by using the Meta-Clustering Technique which means combination of more than one concept for clustering the data. Our experimental result says if a user gives a wrong spelling then at least one output will be common if he will give the correct spell. Our proposed searching tool works in the static database but in future it will be able to work in the dynamic database even may be used as 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":"Design and Analysis of Algorithm to Search Documents with Misspelled Input","attachmentId":85720064,"attachmentType":"pdf","work_url":"https://www.academia.edu/78804300/Design_and_Analysis_of_Algorithm_to_Search_Documents_with_Misspelled_Input","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/78804300/Design_and_Analysis_of_Algorithm_to_Search_Documents_with_Misspelled_Input"><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="98604820" 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/98604820/Spelling_Checker_using_Algorithm_Damerau_Levenshtein_Distance_and_Cosine_Similarity">Spelling Checker using Algorithm Damerau Levenshtein Distance and Cosine Similarity</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="261822468" href="https://independent.academia.edu/NurHamidah569">Nur Hamidah</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Sriwijaya Journal of Informatics and Applications, 2020</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 Checker using Algorithm Damerau Levenshtein Distance and Cosine Similarity","attachmentId":99909569,"attachmentType":"pdf","work_url":"https://www.academia.edu/98604820/Spelling_Checker_using_Algorithm_Damerau_Levenshtein_Distance_and_Cosine_Similarity","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/98604820/Spelling_Checker_using_Algorithm_Damerau_Levenshtein_Distance_and_Cosine_Similarity"><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="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="6" data-entity-id="70413118" 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/70413118/Implementation_of_improved_Levenshtein_algorithm_for_spelling_correction_word_candidate_list_generation">Implementation of improved Levenshtein algorithm for spelling correction word candidate list generation</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="60462" href="https://uum.academia.edu/ShahrulAzmiMohdYusof">Shahrul Azmi Mohd Yusof</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2016</p><p class="ds-related-work--abstract ds2-5-body-sm">Candidates’ list generation in spelling correction is a process of finding words from a lexicon that are close to the incorrect word. The most widely used algorithm to generate the candidate list is the Levenshtein algorithm. However, the algorithm consumes high computational cost, especially when there is a large number of spelling errors. The reason is that calculating Levenshtein algorithm includes operations that create an array and fill the cells of this array by comparing the characters of an incorrect word with the characters of a word from a lexicon. Since most lexicons contain millions of words, such operations will be repeated millions of times for each incorrect word in order to generate its candidates’ list. This study proposes an improved Levenshtein algorithm that reduces the operation steps in comparing characters between the query and lexicon words. Experimental results show that the proposed algorithm outperformed the Levenshtein algorithm in terms of processing tim...</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":"Implementation of improved Levenshtein algorithm for spelling correction word candidate list generation","attachmentId":80176925,"attachmentType":"pdf","work_url":"https://www.academia.edu/70413118/Implementation_of_improved_Levenshtein_algorithm_for_spelling_correction_word_candidate_list_generation","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/70413118/Implementation_of_improved_Levenshtein_algorithm_for_spelling_correction_word_candidate_list_generation"><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="68916975" 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/68916975/A_Survey_of_Spelling_Error_Detection_and_Correction_Techniques">A Survey of Spelling Error Detection and Correction 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="193644425" href="https://independent.academia.edu/RitikaMishra34">Ritika Mishra</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2013</p><p class="ds-related-work--abstract ds2-5-body-sm">Spelling Correction is a process of detecting and sometimes providing suggestions for incorrectly spelled words in a text. Spell Checker is an application program that flags words in a document that may not be spelled correctly. Spell Checker may be stand-alone capable of operating on a block a text such as word processor, electronic dictionary. When some text is given as an input to spell checker, it list outs the incorrect words separately by checking their availability in the dictionary. Finally it provides the suggestions for the incorrect words from the dictionary. This survey paper covers almost all the spelling correction techniques. Keywords— Spell Checker, NLP, Error detection techniques, Error correction techniques.</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 Spelling Error Detection and Correction Techniques","attachmentId":79218601,"attachmentType":"pdf","work_url":"https://www.academia.edu/68916975/A_Survey_of_Spelling_Error_Detection_and_Correction_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/68916975/A_Survey_of_Spelling_Error_Detection_and_Correction_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="8" 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 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":"Learning a Spelling Error Model from Search Query Logs","attachmentId":33444293,"attachmentType":"pdf","work_url":"https://www.academia.edu/6725503/Learning_a_Spelling_Error_Model_from_Search_Query_Logs","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/6725503/Learning_a_Spelling_Error_Model_from_Search_Query_Logs"><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="89388685" 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/89388685/Studying_the_effect_and_treatment_of_misspelled_queries_in_Cross_Language_Information_Retrieval">Studying the effect and treatment of misspelled queries in Cross-Language 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="3227654" href="https://coruna.academia.edu/JesusVilares">Jesus Vilares</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Information Processing &amp; Management, 2016</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":"Studying the effect and treatment of misspelled queries in Cross-Language Information Retrieval","attachmentId":93198952,"attachmentType":"pdf","work_url":"https://www.academia.edu/89388685/Studying_the_effect_and_treatment_of_misspelled_queries_in_Cross_Language_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/89388685/Studying_the_effect_and_treatment_of_misspelled_queries_in_Cross_Language_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":30680850,"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":30680850,"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_30680850" style="display: none"><div class="scribd--being-converted-container">This document is currently being converted. 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