{"id":"https://openalex.org/W2031870345","doi":"https://doi.org/10.1145/2675744.2675746","title":"Na\u00efve Bayes classifier for Hindi word sense disambiguation","display_name":"Na\u00efve Bayes classifier for Hindi word sense disambiguation","publication_year":2014,"publication_date":"2014-10-09","ids":{"openalex":"https://openalex.org/W2031870345","doi":"https://doi.org/10.1145/2675744.2675746","mag":"2031870345"},"language":"en","primary_location":{"id":"doi:10.1145/2675744.2675746","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2675744.2675746","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM India Computing Conference","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071461097","display_name":"Satyendr Singh","orcid":"https://orcid.org/0000-0001-9602-5728"},"institutions":[{"id":"https://openalex.org/I168893459","display_name":"University of Allahabad","ror":"https://ror.org/03vrx7m55","country_code":"IN","type":"education","lineage":["https://openalex.org/I168893459"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Satyendr Singh","raw_affiliation_strings":["University of Allahabad, Allahabad, India","University of Allahabad, Allahabad, INDIA"],"affiliations":[{"raw_affiliation_string":"University of Allahabad, Allahabad, India","institution_ids":["https://openalex.org/I168893459"]},{"raw_affiliation_string":"University of Allahabad, Allahabad, INDIA","institution_ids":["https://openalex.org/I168893459"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021143956","display_name":"Tanveer J. Siddiqui","orcid":"https://orcid.org/0000-0002-8190-0646"},"institutions":[{"id":"https://openalex.org/I168893459","display_name":"University of Allahabad","ror":"https://ror.org/03vrx7m55","country_code":"IN","type":"education","lineage":["https://openalex.org/I168893459"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Tanveer J. Siddiqui","raw_affiliation_strings":["University of Allahabad, Allahabad, India","University of Allahabad, Allahabad, INDIA"],"affiliations":[{"raw_affiliation_string":"University of Allahabad, Allahabad, India","institution_ids":["https://openalex.org/I168893459"]},{"raw_affiliation_string":"University of Allahabad, Allahabad, INDIA","institution_ids":["https://openalex.org/I168893459"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049689320","display_name":"Sunil Kumar Sharma","orcid":"https://orcid.org/0000-0002-1732-2677"},"institutions":[{"id":"https://openalex.org/I1341412227","display_name":"IBM (United States)","ror":"https://ror.org/05hh8d621","country_code":"US","type":"company","lineage":["https://openalex.org/I1341412227"]},{"id":"https://openalex.org/I4210103279","display_name":"IBM Research - India","ror":"https://ror.org/014wt7r80","country_code":"IN","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210103279","https://openalex.org/I4210114115"]}],"countries":["IN","US"],"is_corresponding":false,"raw_author_name":"Sunil K. Sharma","raw_affiliation_strings":["IBM, India","IBM - India"],"affiliations":[{"raw_affiliation_string":"IBM, India","institution_ids":["https://openalex.org/I4210103279"]},{"raw_affiliation_string":"IBM - India","institution_ids":["https://openalex.org/I1341412227"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5071461097"],"corresponding_institution_ids":["https://openalex.org/I168893459"],"apc_list":null,"apc_paid":null,"fwci":2.4541,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.90639593,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10181","display_name":"Natural Language Processing Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hindi","display_name":"Hindi","score":0.8299327492713928},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7696391940116882},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7638001441955566},{"id":"https://openalex.org/keywords/noun","display_name":"Noun","score":0.7009907364845276},{"id":"https://openalex.org/keywords/word-sense-disambiguation","display_name":"Word-sense disambiguation","score":0.662852942943573},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6372157335281372},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6210092902183533},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.6127399206161499},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4556574821472168},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.45345044136047363},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4274039566516876},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3971860408782959},{"id":"https://openalex.org/keywords/wordnet","display_name":"WordNet","score":0.17915818095207214},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1572566032409668}],"concepts":[{"id":"https://openalex.org/C519982507","wikidata":"https://www.wikidata.org/wiki/Q1568","display_name":"Hindi","level":2,"score":0.8299327492713928},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7696391940116882},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7638001441955566},{"id":"https://openalex.org/C121934690","wikidata":"https://www.wikidata.org/wiki/Q1084","display_name":"Noun","level":2,"score":0.7009907364845276},{"id":"https://openalex.org/C51646954","wikidata":"https://www.wikidata.org/wiki/Q48522","display_name":"Word-sense disambiguation","level":3,"score":0.662852942943573},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6372157335281372},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6210092902183533},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.6127399206161499},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4556574821472168},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.45345044136047363},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4274039566516876},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3971860408782959},{"id":"https://openalex.org/C157659113","wikidata":"https://www.wikidata.org/wiki/Q533822","display_name":"WordNet","level":2,"score":0.17915818095207214},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1572566032409668},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2675744.2675746","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2675744.2675746","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 7th ACM India Computing Conference","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W183521441","https://openalex.org/W1489348810","https://openalex.org/W1506819108","https://openalex.org/W1539122336","https://openalex.org/W1555805532","https://openalex.org/W1795234945","https://openalex.org/W1970308971","https://openalex.org/W1977182536","https://openalex.org/W1989186855","https://openalex.org/W2060704947","https://openalex.org/W2062491967","https://openalex.org/W2137460447","https://openalex.org/W2403515192","https://openalex.org/W2785717676","https://openalex.org/W4285719527","https://openalex.org/W4365799834"],"related_works":["https://openalex.org/W2384553807","https://openalex.org/W1557888283","https://openalex.org/W3089999372","https://openalex.org/W2265245145","https://openalex.org/W3110423299","https://openalex.org/W4312229285","https://openalex.org/W2738278463","https://openalex.org/W4308939443","https://openalex.org/W4299528489","https://openalex.org/W4401555724"],"abstract_inverted_index":{"This":[0],"paper":[1],"investigates":[2],"Na\u00efve":[3],"Bayes":[4],"(NB)":[5],"classifier":[6,93],"for":[7],"Hindi":[8,42,48],"Word":[9],"Sense":[10],"Disambiguation":[11],"(WSD)":[12],"utilizing":[13,71,109],"eleven":[14],"features.":[15],"The":[16,79],"features":[17],"used":[18],"in":[19,61,73,111],"the":[20,112],"experiment":[21],"includes":[22],"local":[23],"context,":[24],"collocations,":[25],"unordered":[26,57,99],"list":[27,58,100],"of":[28,45,52,59,68,91,101,106],"words,":[29],"nouns":[30,72],"and":[31],"vibhaktis.":[32],"Evaluation":[33],"is":[34],"done":[35],"on":[36],"a":[37],"manually":[38],"created":[39],"sense":[40],"annotated":[41],"corpus":[43],"consisting":[44],"60":[46],"polysemous":[47],"nouns.":[49],"A":[50],"precision":[51,67,105],"77.52%":[53],"was":[54],"observed,":[55],"using":[56],"words":[60],"feature":[62,74,113],"vector.":[63,114],"We":[64,103],"obtained":[65,104],"maximum":[66],"86.11%":[69],"by":[70,84,108],"vector":[75],"after":[76],"applying":[77],"morphology.":[78],"experimental":[80],"results":[81],"demonstrates":[82],"that":[83],"adding":[85],"more":[86],"rich":[87],"features,":[88],"WSD":[89],"accuracy":[90],"NB":[92],"can":[94],"be":[95],"significantly":[96],"improved":[97],"over":[98],"words.":[102],"56.49%,":[107],"vibhaktis":[110]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}