{"id":"https://openalex.org/W3032227162","doi":"https://doi.org/10.3233/ida-194669","title":"Estimating a one-class naive Bayes text classifier","display_name":"Estimating a one-class naive Bayes text classifier","publication_year":2020,"publication_date":"2020-05-21","ids":{"openalex":"https://openalex.org/W3032227162","doi":"https://doi.org/10.3233/ida-194669","mag":"3032227162"},"language":"en","primary_location":{"id":"doi:10.3233/ida-194669","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-194669","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-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/A5081101711","display_name":"Yihong Zhang","orcid":"https://orcid.org/0000-0002-4758-9911"},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"Osaka University","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Yihong Zhang","raw_affiliation_strings":["Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University, Osaka 565-0871, Japan"],"affiliations":[{"raw_affiliation_string":"Department of Multimedia Engineering, Graduate School of Information Science and Technology, Osaka University, Osaka 565-0871, Japan","institution_ids":["https://openalex.org/I98285908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079733597","display_name":"Adam Jatowt","orcid":"https://orcid.org/0000-0001-7235-0665"},"institutions":[{"id":"https://openalex.org/I22299242","display_name":"Kyoto University","ror":"https://ror.org/02kpeqv85","country_code":"JP","type":"education","lineage":["https://openalex.org/I22299242"]},{"id":"https://openalex.org/I39012071","display_name":"Kyoto College of Graduate Studies for Informatics","ror":"https://ror.org/05mzj8a56","country_code":"JP","type":"education","lineage":["https://openalex.org/I39012071"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Adam Jatowt","raw_affiliation_strings":["Department of Social Informatics, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan","E-mail:"],"affiliations":[{"raw_affiliation_string":"Department of Social Informatics, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan","institution_ids":["https://openalex.org/I39012071","https://openalex.org/I22299242"]},{"raw_affiliation_string":"E-mail:","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5081101711"],"corresponding_institution_ids":["https://openalex.org/I98285908"],"apc_list":null,"apc_paid":null,"fwci":1.0605,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.81848185,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"24","issue":"3","first_page":"567","last_page":"579"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","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/T11550","display_name":"Text and Document Classification Technologies","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/T12535","display_name":"Machine Learning and Data Classification","score":0.9945999979972839,"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":0.992900013923645,"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/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.8404089212417603},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.7791513800621033},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7110667824745178},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7022210359573364},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6735647916793823},{"id":"https://openalex.org/keywords/bayes-classifier","display_name":"Bayes classifier","score":0.6224470138549805},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5837547183036804},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5150260925292969},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.4165748357772827},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4152403771877289},{"id":"https://openalex.org/keywords/bayes-error-rate","display_name":"Bayes error rate","score":0.41459816694259644},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.19570830464363098}],"concepts":[{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.8404089212417603},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.7791513800621033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7110667824745178},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7022210359573364},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6735647916793823},{"id":"https://openalex.org/C185207860","wikidata":"https://www.wikidata.org/wiki/Q17004744","display_name":"Bayes classifier","level":4,"score":0.6224470138549805},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5837547183036804},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5150260925292969},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.4165748357772827},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4152403771877289},{"id":"https://openalex.org/C143809311","wikidata":"https://www.wikidata.org/wiki/Q4874458","display_name":"Bayes error rate","level":5,"score":0.41459816694259644},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.19570830464363098}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.3233/ida-194669","is_oa":false,"landing_page_url":"https://doi.org/10.3233/ida-194669","pdf_url":null,"source":{"id":"https://openalex.org/S2498839158","display_name":"Intelligent Data Analysis","issn_l":"1088-467X","issn":["1088-467X","1571-4128"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Data Analysis","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W22461475","https://openalex.org/W641710284","https://openalex.org/W797920393","https://openalex.org/W1559054844","https://openalex.org/W1590495275","https://openalex.org/W1861993554","https://openalex.org/W1987971958","https://openalex.org/W2012914116","https://openalex.org/W2052635433","https://openalex.org/W2053968437","https://openalex.org/W2056234582","https://openalex.org/W2067624665","https://openalex.org/W2123958887","https://openalex.org/W2124499489","https://openalex.org/W2125017820","https://openalex.org/W2131904035","https://openalex.org/W2132870739","https://openalex.org/W2134510195","https://openalex.org/W2142047467","https://openalex.org/W2147654806","https://openalex.org/W2153635508","https://openalex.org/W2566898791","https://openalex.org/W2597819602","https://openalex.org/W2618285999","https://openalex.org/W2788085070","https://openalex.org/W3104422614","https://openalex.org/W6600212061","https://openalex.org/W6630370885","https://openalex.org/W6679539681"],"related_works":["https://openalex.org/W2374047926","https://openalex.org/W2360982908","https://openalex.org/W2394466068","https://openalex.org/W145653800","https://openalex.org/W2393473353","https://openalex.org/W4312866165","https://openalex.org/W108287568","https://openalex.org/W179179905","https://openalex.org/W4251019512","https://openalex.org/W2780177025"],"abstract_inverted_index":{"Nowadays":[0],"more":[1,3,150],"and":[2,31,80,117,142],"information":[4],"extraction":[5],"projects":[6],"need":[7],"to":[8,18,22,41,47,114,154],"classify":[9,19],"large":[10],"amounts":[11],"of":[12,58,106,125],"text":[13,20],"data.":[14,82,111],"The":[15],"common":[16],"way":[17],"is":[21,39],"build":[23],"a":[24,60,89],"supervised":[25],"classifier":[26,62,75,92],"trained":[27],"on":[28,72,109],"human-labeled":[29],"positive":[30,43,66,78],"negative":[32,49],"examples.":[33,50],"In":[34,51,83],"many":[35],"cases,":[36],"however,":[37],"it":[38],"easy":[40],"label":[42,48],"examples,":[44],"but":[45],"hard":[46],"this":[52,84],"paper,":[53,85],"we":[54,86],"address":[55],"the":[56,65,103,107,126,147],"problem":[57],"building":[59,73],"one-class":[61,74,91,95],"when":[63],"only":[64],"examples":[67,79],"are":[68],"labeled.":[69],"Previous":[70],"works":[71],"mostly":[76],"use":[77,115],"unlabeled":[81],"show":[87,133],"that":[88,134],"configurable":[90],"such":[93],"as":[94],"naive":[96],"Bayes":[97],"can":[98],"be":[99],"optimized":[100],"by":[101,149],"examining":[102],"clustering":[104,123],"quality":[105,119,124],"classification":[108,140],"target":[110],"We":[112],"propose":[113],"existing":[116],"new":[118],"scores":[120],"for":[121],"determining":[122],"classification.":[127],"Experimental":[128],"analysis":[129],"with":[130],"real-world":[131],"data":[132],"our":[135],"approach":[136],"generally":[137],"achieves":[138],"high":[139],"accuracy,":[141],"in":[143],"some":[144],"cases":[145],"improves":[146],"accuracy":[148],"than":[151],"10%":[152],"compared":[153],"state-of-art":[155],"baselines.":[156]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
