{"id":"https://openalex.org/W2111700528","doi":"https://doi.org/10.1145/1015330.1015350","title":"Co-EM support vector learning","display_name":"Co-EM support vector learning","publication_year":2004,"publication_date":"2004-01-01","ids":{"openalex":"https://openalex.org/W2111700528","doi":"https://doi.org/10.1145/1015330.1015350","mag":"2111700528"},"language":"en","primary_location":{"id":"doi:10.1145/1015330.1015350","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1015330.1015350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Twenty-first international conference on Machine learning  - ICML '04","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/A5049583553","display_name":"Ulf Brefeld","orcid":"https://orcid.org/0000-0001-9600-6463"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Ulf Brefeld","raw_affiliation_strings":["Humboldt-Universit\u00e4t zu Berlin, Berlin, Germany","[Humboldt Universitat zu Berlin, Berlin, Germany]"],"affiliations":[{"raw_affiliation_string":"Humboldt-Universit\u00e4t zu Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I39343248"]},{"raw_affiliation_string":"[Humboldt Universitat zu Berlin, Berlin, Germany]","institution_ids":["https://openalex.org/I39343248"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007427935","display_name":"Tobias Scheffer","orcid":"https://orcid.org/0000-0003-4405-7925"},"institutions":[{"id":"https://openalex.org/I39343248","display_name":"Humboldt-Universit\u00e4t zu Berlin","ror":"https://ror.org/01hcx6992","country_code":"DE","type":"education","lineage":["https://openalex.org/I39343248"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tobias Scheffer","raw_affiliation_strings":["Humboldt-Universit\u00e4t zu Berlin, Berlin, Germany","[Humboldt Universitat zu Berlin, Berlin, Germany]"],"affiliations":[{"raw_affiliation_string":"Humboldt-Universit\u00e4t zu Berlin, Berlin, Germany","institution_ids":["https://openalex.org/I39343248"]},{"raw_affiliation_string":"[Humboldt Universitat zu Berlin, Berlin, Germany]","institution_ids":["https://openalex.org/I39343248"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5049583553"],"corresponding_institution_ids":["https://openalex.org/I39343248"],"apc_list":null,"apc_paid":null,"fwci":12.0153,"has_fulltext":false,"cited_by_count":200,"citation_normalized_percentile":{"value":0.98487552,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"16","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9969000220298767,"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":0.9969000220298767,"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":0.9915000200271606,"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":0.9908999800682068,"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/support-vector-machine","display_name":"Support vector machine","score":0.7436275482177734},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6960002779960632},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6867775917053223},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.643925130367279},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6303411722183228},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.5592576265335083},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.5506892204284668},{"id":"https://openalex.org/keywords/co-training","display_name":"Co-training","score":0.5320765972137451},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5067878365516663},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5040120482444763},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.47478148341178894},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4227885603904724}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7436275482177734},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6960002779960632},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6867775917053223},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.643925130367279},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6303411722183228},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.5592576265335083},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.5506892204284668},{"id":"https://openalex.org/C2776959682","wikidata":"https://www.wikidata.org/wiki/Q17005296","display_name":"Co-training","level":3,"score":0.5320765972137451},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5067878365516663},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5040120482444763},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.47478148341178894},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4227885603904724}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1145/1015330.1015350","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1015330.1015350","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Twenty-first international conference on Machine learning  - ICML '04","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.leuphana.de:openaire_cris_publications/a4397ba8-9d66-4a08-a681-7898eede574b","is_oa":false,"landing_page_url":"http://fis.leuphana.de/de/publications/coem-support-vector-learning(a4397ba8-9d66-4a08-a681-7898eede574b).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400489","display_name":"Multilingual Matters (Channel View Publications)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Brefeld, U & Scheffer, T 2004, Co-EM Support Vector learning. in Proceeding ICML '04 Proceedings of the twenty-first international conference on Machine learning. Proceedings, Twenty-First International Conference on Machine Learning, ICML 2004, Association for Computing Machinery, Inc, New York, pp. 121-128, 21st International Conference on Machine Learning - 2004, Banff, Canada, 31.12.04. https://doi.org/10.1145/1015330.1015350","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.1.6487","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.1.6487","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.aicml.cs.ualberta.ca/banff04/icml/pages/papers/96.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.119.928","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.119.928","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www2.informatik.hu-berlin.de/~brefeld/publications/coemsvm.pdf","raw_type":"text"},{"id":"pmh:oai:pure.leuphana.de:publications/a4397ba8-9d66-4a08-a681-7898eede574b","is_oa":false,"landing_page_url":"http://fox.leuphana.de/portal/de/publications/coem-support-vector-learning(a4397ba8-9d66-4a08-a681-7898eede574b).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400489","display_name":"Multilingual Matters (Channel View Publications)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Brefeld, U & Scheffer, T 2004, Co-EM Support Vector learning. in Proceeding ICML '04 Proceedings of the twenty-first international conference on Machine learning. Proceedings, Twenty-First International Conference on Machine Learning, ICML 2004, Association for Computing Machinery, Inc, New York, pp. 121-128, 21st International Conference on Machine Learning - 2004, Banff, Canada, 31.12.04. https://doi.org/10.1145/1015330.1015350","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8500000238418579,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W17326248","https://openalex.org/W1486331811","https://openalex.org/W1505796919","https://openalex.org/W1514707997","https://openalex.org/W1524761913","https://openalex.org/W1555708985","https://openalex.org/W1566499617","https://openalex.org/W1574877594","https://openalex.org/W1576520375","https://openalex.org/W1595222087","https://openalex.org/W1604938182","https://openalex.org/W1649863237","https://openalex.org/W2037603696","https://openalex.org/W2039609561","https://openalex.org/W2048679005","https://openalex.org/W2049633694","https://openalex.org/W2060183742","https://openalex.org/W2097089247","https://openalex.org/W2107008379","https://openalex.org/W2111557120","https://openalex.org/W2148603752","https://openalex.org/W2155653793","https://openalex.org/W2156909104","https://openalex.org/W2158485347","https://openalex.org/W2170569305","https://openalex.org/W2561879720","https://openalex.org/W2785349534"],"related_works":["https://openalex.org/W2133556223","https://openalex.org/W2098708659","https://openalex.org/W2797776314","https://openalex.org/W4303683898","https://openalex.org/W1505796919","https://openalex.org/W2087783760","https://openalex.org/W2378187833","https://openalex.org/W2130553454","https://openalex.org/W2504719182","https://openalex.org/W121244246"],"abstract_inverted_index":{"Multi-view":[0],"algorithms,":[1],"such":[2,105],"as":[3,106],"co-training":[4,24],"and":[5,19,38,65,82],"co-EM,":[6],"utilize":[7],"unlabeled":[8],"data":[9],"when":[10],"the":[11,31,71,84,97,113],"available":[12],"attributes":[13],"can":[14],"be":[15],"split":[16],"into":[17,61],"independent":[18],"compatible":[20],"subsets.":[21],"Co-EM":[22],"outperforms":[23],"for":[25],"many":[26],"problems,":[27,104],"but":[28],"it":[29],"requires":[30],"underlying":[32,99],"learner":[33],"to":[34,39],"estimate":[35],"class":[36],"probabilities,":[37],"learn":[40],"from":[41],"probabilistically":[42],"labeled":[43],"data.":[44],"Therefore,":[45],"co-EM":[46,68],"has":[47],"so":[48,118],"far":[49],"only":[50],"been":[51],"studied":[52],"with":[53],"naive":[54],"Bayesian":[55],"learners.":[56],"We":[57,75],"cast":[58],"linear":[59],"classifiers":[60],"a":[62,67],"probabilistic":[63],"framework":[64],"develop":[66],"version":[69],"of":[70,86,96],"Support":[72],"Vector":[73],"Machine.":[74],"conduct":[76],"experiments":[77],"on":[78],"text":[79],"classification":[80],"problems":[81],"compare":[83],"family":[85],"semi-supervised":[87],"support":[88],"vector":[89],"algorithms":[90],"under":[91],"different":[92],"conditions,":[93],"including":[94],"violations":[95],"assumptions":[98],"multi-view":[100],"learning.":[101],"For":[102],"some":[103],"course":[107],"web":[108],"page":[109],"classification,":[110],"we":[111],"observe":[112],"most":[114],"accurate":[115],"results":[116],"reported":[117],"far.":[119]},"counts_by_year":[{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":9},{"year":2017,"cited_by_count":12},{"year":2016,"cited_by_count":12},{"year":2015,"cited_by_count":15},{"year":2014,"cited_by_count":10},{"year":2013,"cited_by_count":12},{"year":2012,"cited_by_count":18}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
