{"id":"https://openalex.org/W2765972116","doi":"https://doi.org/10.1145/3137114","title":"Vertical Ensemble Co-Training for Text Classification","display_name":"Vertical Ensemble Co-Training for Text Classification","publication_year":2017,"publication_date":"2017-10-25","ids":{"openalex":"https://openalex.org/W2765972116","doi":"https://doi.org/10.1145/3137114","mag":"2765972116"},"language":"en","primary_location":{"id":"doi:10.1145/3137114","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3137114","pdf_url":null,"source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","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/A5044390999","display_name":"Gilad Katz","orcid":"https://orcid.org/0000-0001-9478-7550"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Gilad Katz","raw_affiliation_strings":["Ben-Gurion University of the Negev, Beer Sheve, Israel"],"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev, Beer Sheve, Israel","institution_ids":["https://openalex.org/I124227911"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089085275","display_name":"Cornelia Caragea","orcid":"https://orcid.org/0000-0002-5664-2163"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Cornelia Caragea","raw_affiliation_strings":["University of North Texas, Denton, TX"],"affiliations":[{"raw_affiliation_string":"University of North Texas, Denton, TX","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002391103","display_name":"Asaf Shabtai","orcid":"https://orcid.org/0000-0003-0630-4059"},"institutions":[{"id":"https://openalex.org/I124227911","display_name":"Ben-Gurion University of the Negev","ror":"https://ror.org/05tkyf982","country_code":"IL","type":"education","lineage":["https://openalex.org/I124227911"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Asaf Shabtai","raw_affiliation_strings":["Ben-Gurion University of the Negev, Beer Sheve, Israel"],"affiliations":[{"raw_affiliation_string":"Ben-Gurion University of the Negev, Beer Sheve, Israel","institution_ids":["https://openalex.org/I124227911"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5044390999"],"corresponding_institution_ids":["https://openalex.org/I124227911"],"apc_list":null,"apc_paid":null,"fwci":0.5851,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.76309822,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"9","issue":"2","first_page":"1","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12535","display_name":"Machine Learning and Data Classification","score":0.9998999834060669,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9998999834060669,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9995999932289124,"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":0.9991000294685364,"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/computer-science","display_name":"Computer science","score":0.8803458213806152},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6387102603912354},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.6281026601791382},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6223893761634827},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5985645055770874},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.5551438927650452},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5380053520202637},{"id":"https://openalex.org/keywords/co-training","display_name":"Co-training","score":0.5032042860984802},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37518274784088135},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33128389716148376},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.26660728454589844}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8803458213806152},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6387102603912354},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.6281026601791382},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6223893761634827},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5985645055770874},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.5551438927650452},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5380053520202637},{"id":"https://openalex.org/C2776959682","wikidata":"https://www.wikidata.org/wiki/Q17005296","display_name":"Co-training","level":3,"score":0.5032042860984802},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37518274784088135},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33128389716148376},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.26660728454589844},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3137114","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3137114","pdf_url":null,"source":{"id":"https://openalex.org/S2492086750","display_name":"ACM Transactions on Intelligent Systems and Technology","issn_l":"2157-6904","issn":["2157-6904","2157-6912"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Intelligent Systems and Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.7200000286102295,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":64,"referenced_works":["https://openalex.org/W25352335","https://openalex.org/W71104953","https://openalex.org/W87822204","https://openalex.org/W779494576","https://openalex.org/W1479735445","https://openalex.org/W1505796919","https://openalex.org/W1534477342","https://openalex.org/W1566499617","https://openalex.org/W1590700995","https://openalex.org/W1595222087","https://openalex.org/W1607035479","https://openalex.org/W1618905105","https://openalex.org/W1840338487","https://openalex.org/W1885010341","https://openalex.org/W1889038981","https://openalex.org/W1906766771","https://openalex.org/W1967821728","https://openalex.org/W1975196881","https://openalex.org/W1980086685","https://openalex.org/W1988790447","https://openalex.org/W1990334093","https://openalex.org/W2037603696","https://openalex.org/W2041741035","https://openalex.org/W2048679005","https://openalex.org/W2059342086","https://openalex.org/W2096507791","https://openalex.org/W2097089247","https://openalex.org/W2102539288","https://openalex.org/W2104331347","https://openalex.org/W2104660959","https://openalex.org/W2107008379","https://openalex.org/W2111700528","https://openalex.org/W2113459411","https://openalex.org/W2128073546","https://openalex.org/W2128614648","https://openalex.org/W2133348086","https://openalex.org/W2133556223","https://openalex.org/W2133990480","https://openalex.org/W2134656491","https://openalex.org/W2134696506","https://openalex.org/W2137210549","https://openalex.org/W2137806537","https://openalex.org/W2145073242","https://openalex.org/W2153927146","https://openalex.org/W2161336914","https://openalex.org/W2165396616","https://openalex.org/W2166706824","https://openalex.org/W2167660864","https://openalex.org/W2182361439","https://openalex.org/W2213612645","https://openalex.org/W2215421138","https://openalex.org/W2426031434","https://openalex.org/W2486168876","https://openalex.org/W2556522401","https://openalex.org/W2560674852","https://openalex.org/W2591957553","https://openalex.org/W2911964244","https://openalex.org/W2912934387","https://openalex.org/W2997546679","https://openalex.org/W4212883601","https://openalex.org/W4250579203","https://openalex.org/W4285719527","https://openalex.org/W4299828299","https://openalex.org/W6681651645"],"related_works":["https://openalex.org/W2797776314","https://openalex.org/W4303683898","https://openalex.org/W1505796919","https://openalex.org/W2087783760","https://openalex.org/W2130553454","https://openalex.org/W121244246","https://openalex.org/W1201517337","https://openalex.org/W4317548404","https://openalex.org/W2766321935","https://openalex.org/W3183551524"],"abstract_inverted_index":{"High-quality,":[0],"labeled":[1,23],"data":[2,24,51],"is":[3,25],"essential":[4],"for":[5,96],"successfully":[6],"applying":[7],"machine":[8],"learning":[9],"methods":[10],"to":[11,29,52,57,80,125],"real-world":[12],"text":[13],"classification":[14,104],"problems.":[15],"However,":[16],"in":[17,61,156],"many":[18],"cases,":[19],"the":[20,32,78,92,160],"amount":[21],"of":[22,31,49,77,84,119,153],"very":[26,59],"small":[27],"compared":[28,158],"that":[30,115],"unlabeled,":[33],"and":[34,41],"labeling":[35,97,127],"additional":[36,140],"samples":[37],"could":[38],"be":[39,58],"expensive":[40],"time":[42],"consuming.":[43],"Co-training":[44],"algorithms,":[45],"which":[46,131],"make":[47],"use":[48],"unlabeled":[50,85],"improve":[53,103,126],"classification,":[54],"have":[55],"proven":[56],"effective":[60],"such":[62],"cases.":[63],"Generally,":[64],"co-training":[65,113,162],"algorithms":[66],"work":[67],"by":[68],"using":[69],"two":[70,74],"classifiers,":[71],"trained":[72],"on":[73,145],"different":[75,122],"views":[76],"data,":[79,99],"label":[81],"large":[82],"amounts":[83],"data.":[86],"Doing":[87],"so":[88],"can":[89],"help":[90],"minimize":[91],"human":[93],"effort":[94],"required":[95],"new":[98],"as":[100,102],"well":[101],"performance.":[105],"In":[106],"this":[107],"article,":[108],"we":[109,132],"propose":[110],"an":[111,117],"ensemble-based":[112],"approach":[114],"uses":[116],"ensemble":[118,135],"classifiers":[120],"from":[121],"training":[123],"iterations":[124],"accuracy.":[128],"This":[129],"approach,":[130],"call":[133],"vertical":[134],",":[136],"incurs":[137],"almost":[138],"no":[139],"computational":[141],"cost.":[142],"Experiments":[143],"conducted":[144],"six":[146],"textual":[147],"datasets":[148],"show":[149],"a":[150],"significant":[151],"improvement":[152],"over":[154],"45%":[155],"AUC":[157],"with":[159],"original":[161],"algorithm.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}