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{"work":{"id":451350,"created_at":"2011-02-21T17:09:42.829-08:00","from_world_paper_id":2448889,"updated_at":"2025-02-02T17:15:57.855-08:00","_data":{"publisher":"nada.kth.se","ai_abstract":"This paper discusses the implementation and applications of a spelling correction algorithm tailored for Swedish, leveraging Bloom filters to address the challenges posed by the language's morphological richness and compound word formation. The method is named STAVA and emphasizes the ranking of spelling correction suggestions using quantitative linguistic methods. The paper also explores additional applications such as part-of-speech lexicon creation and search query correction.","ai_title_tag":"STAVA: A Swedish Spelling Correction Algorithm","publication_date":"2001,1,1","publication_name":"Text as a Linguistic …"},"document_type":"paper","pre_hit_view_count_baseline":0,"quality":"high","language":"en","title":"Implementation Aspects and Applications of a Spelling Correction Algorithm","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [339543]; 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":3484770,"attachmentType":"pdf"}"><img alt="First page of “Implementation Aspects and Applications of a Spelling Correction Algorithm”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/3484770/mini_magick20190427-15803-ndlst7.png?1556381188" /><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">Implementation Aspects and Applications of a Spelling Correction Algorithm</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="339543" href="https://kth.academia.edu/ViggoKann"><img alt="Profile image of Viggo Kann" class="ds-work-card--author-avatar" src="//a.academia-assets.com/images/s65_no_pic.png" />Viggo Kann</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">2001, Text as a Linguistic …</p><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">18 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 = 451350; const worksViewsPath = "/v0/works/views?subdomain_param=api&work_ids%5B%5D=451350"; 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--detail ds2-5-body-md">AI-generated Abstract</p><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">This paper discusses the implementation and applications of a spelling correction algorithm tailored for Swedish, leveraging Bloom filters to address the challenges posed by the language's morphological richness and compound word formation. The method is named STAVA and emphasizes the ranking of spelling correction suggestions using quantitative linguistic methods. The paper also explores additional applications such as part-of-speech lexicon creation and search query correction.</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":3484770,"attachmentType":"pdf","workUrl":"https://www.academia.edu/451350/Implementation_Aspects_and_Applications_of_a_Spelling_Correction_Algorithm"}">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":3484770,"attachmentType":"pdf","workUrl":"https://www.academia.edu/451350/Implementation_Aspects_and_Applications_of_a_Spelling_Correction_Algorithm"}"><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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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="2" 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="3" data-entity-id="56467796" 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/56467796/Survey_of_Automatic_Spelling_Correction">Survey of Automatic 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="160433363" href="https://tuke.academia.edu/MatusPleva">Matus Pleva</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Electronics</p><p class="ds-related-work--abstract ds2-5-body-sm">Automatic spelling correction has been receiving sustained research attention. Although each article contains a brief introduction to the topic, there is a lack of work that would summarize the theoretical framework and provide an overview of the approaches developed so far. Our survey selected papers about spelling correction indexed in Scopus and Web of Science from 1991 to 2019. The first group uses a set of rules designed in advance. The second group uses an additional model of context. The third group of automatic spelling correction systems in the survey can adapt its model to the given problem. The summary tables show the application area, language, string metrics, and context model for each system. The survey describes selected approaches in a common theoretical framework based on Shannon’s noisy channel. A separate section describes evaluation methods and benchmarks.</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":"Survey of Automatic Spelling Correction","attachmentId":71840327,"attachmentType":"pdf","work_url":"https://www.academia.edu/56467796/Survey_of_Automatic_Spelling_Correction","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/56467796/Survey_of_Automatic_Spelling_Correction"><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="6782096" 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/6782096/Revised_N_Gram_based_automatic_spelling_correction_tool_to_improve_retrieval_effectiveness">Revised N-Gram based automatic spelling correction tool to improve retrieval effectiveness</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="11204545" href="https://fiz-karlsruhe.academia.edu/FaragSaad">Farag Saad</a></div><p class="ds-related-work--abstract ds2-5-body-sm">We present a language-independent spell-checker that is based on an enhancement of the n-gram model. The spell checker is proposing correction suggestions by selecting the most promising candidates from a ranked list of correction candidates that is derived based on n-gram statistics and lexical resources. Besides motivating and describing the developed techniques, we briefly discuss the use of the proposed approach in an application for keyword-and semantic-based search support. In addition, the proposed tool was compared with state-of-the-art spelling correction approaches. The evaluation showed that it outperforms the other methods.</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":"Revised N-Gram based automatic spelling correction tool to improve retrieval effectiveness","attachmentId":33487357,"attachmentType":"pdf","work_url":"https://www.academia.edu/6782096/Revised_N_Gram_based_automatic_spelling_correction_tool_to_improve_retrieval_effectiveness","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/6782096/Revised_N_Gram_based_automatic_spelling_correction_tool_to_improve_retrieval_effectiveness"><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="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="171721299" href="https://independent.academia.edu/beeiiaes">beei iaes</a><span>, </span><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></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="6" data-entity-id="2752833" 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/2752833/Improved_Spelling_Error_Detection_and_Correction_for_Arabic">Improved Spelling Error Detection and Correction for Arabic</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="348759" href="https://dcu.academia.edu/MohammedAttia">Mohammed Attia</a></div><p class="ds-related-work--abstract ds2-5-body-sm">ABSTRACT A spelling error detection and correction application is based on three main components: a dictionary (or reference word list), an error model and a language model. While most of the attention in the literature has been directed to the language model, we show how improvements in any of the three components can lead to significant cumulative improvements in the overall performance of the 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":"Improved Spelling Error Detection and Correction for Arabic","attachmentId":30725218,"attachmentType":"pdf","work_url":"https://www.academia.edu/2752833/Improved_Spelling_Error_Detection_and_Correction_for_Arabic","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/2752833/Improved_Spelling_Error_Detection_and_Correction_for_Arabic"><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="17280754" 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/17280754/Unsupervised_Spelling_Correction_for_Slovak">Unsupervised Spelling Correction for Slovak</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="2070391" href="https://tuke.academia.edu/JozefJuh%C3%A1r">Jozef Juhár</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Advances in Electrical and Electronic Engineering, 2013</p><p class="ds-related-work--abstract ds2-5-body-sm">This paper introduces a method to automatically propose and choose a correction for an incorrectly written word in a large text corpus written in Slovak. This task can be described as a process of finding the best matching sequence of correct words to a list of incorrectly spelled words, found in the input. Knowledge base of the classification system -statistics about sequences of correctly typed words and possible corrections for incorrectly typed words can be mathematically described as a hidden Markov model. The best matching sequence of correct words is found using Viterbi algorithm. The system will be evaluated on a manually corrected testing set.</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":"Unsupervised Spelling Correction for Slovak","attachmentId":42272467,"attachmentType":"pdf","work_url":"https://www.academia.edu/17280754/Unsupervised_Spelling_Correction_for_Slovak","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/17280754/Unsupervised_Spelling_Correction_for_Slovak"><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="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="9" data-entity-id="2456279" 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/2456279/Spelling_error_patterns_in_spanish_for_word_processing_applications">Spelling error patterns in spanish for word processing applications</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="1857588" href="https://independent.academia.edu/FloraRamirezBustamante">Flora Ramirez-Bustamante</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Proceedings of the International …, 2006</p><p class="ds-related-work--abstract ds2-5-body-sm">This paper reports findings from the elaboration of a typology of spelling errors for Spanish. It also discusses previous generalizations about spelling error patterns found in other studies and offers new insights on them. The typology is based on the analysis of around 76K misspellings found in real-life texts produced by humans. The main goal of the elaboration of the typology was to help in the implementation of a spell checker that detects context-independent misspellings in general unrestricted texts with the most common confusion pairs (i.e. error/correction pairs) to improve the set of ranked correction candidates for misspellings. We found that spelling errors are language dependent and are closely related to the orthographic rules of each language. The statistical data we provide on spelling error patterns in Spanish and their comparison with other data in other related works are the novel contribution of this paper. In this line, this paper shows that some of the general statements found in the literature about spelling error patterns apply mainly to English and cannot be extrapolated to other languages.</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 error patterns in spanish for word processing applications","attachmentId":33526424,"attachmentType":"pdf","work_url":"https://www.academia.edu/2456279/Spelling_error_patterns_in_spanish_for_word_processing_applications","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/2456279/Spelling_error_patterns_in_spanish_for_word_processing_applications"><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":3484770,"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":3484770,"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_3484770" 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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data-collection-position="3" data-entity-id="12498175" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/12498175/Arabic_Spelling_Error_Detection_and_Correction">Arabic Spelling Error Detection and Correction</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="30994194" href="https://buid.academia.edu/KShaalan">Khaled Shaalan</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Arabic Spelling Error Detection and Correction, 2015</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":"Arabic Spelling Error Detection and 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href="https://ihk.academia.edu/PatriziaPaggio">Patrizia Paggio</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Proceedings of the sixth conference on Applied natural language processing -, 2000</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 and grammar correction for danish in SCARRIE","attachmentId":98346922,"attachmentType":"pdf","work_url":"https://www.academia.edu/96452052/Spelling_and_grammar_correction_for_danish_in_SCARRIE","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/96452052/Spelling_and_grammar_correction_for_danish_in_SCARRIE"><span 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