{"id":"https://openalex.org/W2060777747","doi":"https://doi.org/10.1145/1871437.1871488","title":"A robust semi-supervised classification method for transfer learning","display_name":"A robust semi-supervised classification method for transfer learning","publication_year":2010,"publication_date":"2010-10-26","ids":{"openalex":"https://openalex.org/W2060777747","doi":"https://doi.org/10.1145/1871437.1871488","mag":"2060777747"},"language":"en","primary_location":{"id":"doi:10.1145/1871437.1871488","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1871437.1871488","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM international conference on Information and knowledge management","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/A5043865083","display_name":"Akinori Fujino","orcid":"https://orcid.org/0000-0003-3377-3539"},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Akinori Fujino","raw_affiliation_strings":["NTT Corporation, Soraku-gun, Kyoto, Japan","NTT Corporation, Soraku-gun, Kyoto, Japan#TAB#"],"affiliations":[{"raw_affiliation_string":"NTT Corporation, Soraku-gun, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Corporation, Soraku-gun, Kyoto, Japan#TAB#","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105268757","display_name":"Naonori Ueda","orcid":null},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naonori Ueda","raw_affiliation_strings":["NTT Corporation, Soraku-gun, Kyoto, Japan","NTT Corporation, Soraku-gun, Kyoto, Japan#TAB#"],"affiliations":[{"raw_affiliation_string":"NTT Corporation, Soraku-gun, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Corporation, Soraku-gun, Kyoto, Japan#TAB#","institution_ids":["https://openalex.org/I2251713219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100520423","display_name":"Masaaki Nagata","orcid":null},"institutions":[{"id":"https://openalex.org/I2251713219","display_name":"NTT (Japan)","ror":"https://ror.org/00berct97","country_code":"JP","type":"company","lineage":["https://openalex.org/I2251713219"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaaki Nagata","raw_affiliation_strings":["NTT Corporation, Soraku-gun, Kyoto, Japan","NTT Corporation, Soraku-gun, Kyoto, Japan#TAB#"],"affiliations":[{"raw_affiliation_string":"NTT Corporation, Soraku-gun, Kyoto, Japan","institution_ids":["https://openalex.org/I2251713219"]},{"raw_affiliation_string":"NTT Corporation, Soraku-gun, Kyoto, Japan#TAB#","institution_ids":["https://openalex.org/I2251713219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043865083"],"corresponding_institution_ids":["https://openalex.org/I2251713219"],"apc_list":null,"apc_paid":null,"fwci":1.3531,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.84405123,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"379","last_page":"388"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994999766349792,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9994999766349792,"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":0.9975000023841858,"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":0.9975000023841858,"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/overfitting","display_name":"Overfitting","score":0.8959330916404724},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7788978815078735},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.765576958656311},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7394248247146606},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7367488145828247},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.7230433225631714},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6844321489334106},{"id":"https://openalex.org/keywords/semi-supervised-learning","display_name":"Semi-supervised learning","score":0.6059272289276123},{"id":"https://openalex.org/keywords/linear-classifier","display_name":"Linear classifier","score":0.478263258934021},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4461907148361206},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4454525113105774},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.4173102378845215},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.16557151079177856}],"concepts":[{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.8959330916404724},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7788978815078735},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.765576958656311},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7394248247146606},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7367488145828247},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.7230433225631714},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6844321489334106},{"id":"https://openalex.org/C58973888","wikidata":"https://www.wikidata.org/wiki/Q1041418","display_name":"Semi-supervised learning","level":2,"score":0.6059272289276123},{"id":"https://openalex.org/C139532973","wikidata":"https://www.wikidata.org/wiki/Q2679259","display_name":"Linear classifier","level":3,"score":0.478263258934021},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4461907148361206},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4454525113105774},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.4173102378845215},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.16557151079177856}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1871437.1871488","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1871437.1871488","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM international conference on Information and knowledge management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7599999904632568}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W172698429","https://openalex.org/W304676660","https://openalex.org/W1484860703","https://openalex.org/W1565746575","https://openalex.org/W1574877594","https://openalex.org/W1592796124","https://openalex.org/W1790954942","https://openalex.org/W1966026565","https://openalex.org/W2000987725","https://openalex.org/W2032536435","https://openalex.org/W2034368206","https://openalex.org/W2049633694","https://openalex.org/W2051434435","https://openalex.org/W2081801689","https://openalex.org/W2097089247","https://openalex.org/W2104755048","https://openalex.org/W2111362445","https://openalex.org/W2115191221","https://openalex.org/W2121426455","https://openalex.org/W2122179236","https://openalex.org/W2128313564","https://openalex.org/W2130903752","https://openalex.org/W2136504847","https://openalex.org/W2142114717","https://openalex.org/W2145494108","https://openalex.org/W2153939756","https://openalex.org/W2154326713","https://openalex.org/W2156346614","https://openalex.org/W2156909104","https://openalex.org/W2158108973","https://openalex.org/W2165698076","https://openalex.org/W2231077521","https://openalex.org/W2255883267","https://openalex.org/W2595697910","https://openalex.org/W2997546679","https://openalex.org/W3005100505","https://openalex.org/W4206070857","https://openalex.org/W4296558785"],"related_works":["https://openalex.org/W4390929683","https://openalex.org/W2365028544","https://openalex.org/W4309984931","https://openalex.org/W4282977123","https://openalex.org/W2949671220","https://openalex.org/W2013810580","https://openalex.org/W2186210338","https://openalex.org/W4206276646","https://openalex.org/W2576964996","https://openalex.org/W2371815184"],"abstract_inverted_index":{"The":[0],"transfer":[1,73,112,183],"learning":[2,38,74,113,184],"problem":[3,110,125],"of":[4,23,36,88,144],"designing":[5,46],"good":[6],"classifiers":[7],"with":[8,71,129,181],"a":[9,47,65,78,149],"high":[10],"generalization":[11],"ability":[12],"by":[13,51,56],"using":[14,52,166],"labeled":[15,136],"samples":[16,25,54,139],"whose":[17],"distribution":[18,59],"is":[19,26,86],"different":[20],"from":[21],"that":[22,115,152,173],"test":[24,61,170],"an":[27,108],"important":[28],"and":[29,39,63,81,96,137,157],"challenging":[30],"research":[31],"issue":[32],"in":[33,103,111,118],"the":[34,57,72,89,99,123,130,141,154,174,178],"fields":[35],"machine":[37],"data":[40],"mining.":[41],"This":[42],"paper":[43],"focuses":[44],"on":[45,77],"semi-supervised":[48,66,92],"classifier":[49,93,158],"trained":[50],"unlabeled":[53,138],"drawn":[55],"same":[58],"as":[60],"samples,":[62],"presents":[64],"classification":[67,165],"method":[68,176],"to":[69,126],"deal":[70],"problem,":[75],"based":[76],"hybrid":[79],"discriminative":[80,142],"generative":[82],"model.":[83],"Although":[84],"JESS-CM":[85,179],"one":[87],"most":[90,182],"successful":[91],"design":[94],"frameworks":[95],"has":[97,107],"achieved":[98],"best":[100],"published":[101],"results":[102,162],"NLP":[104],"tasks,":[105],"it":[106],"overfitting":[109,124],"settings":[114],"we":[116],"consider":[117],"this":[119],"paper.":[120],"We":[121,146],"expect":[122],"be":[127],"mitigated":[128],"proposed":[131,175],"method,":[132],"which":[133],"utilizes":[134],"both":[135],"for":[140,163],"training":[143,155],"classifiers.":[145],"also":[147],"present":[148],"refined":[150],"objective":[151],"formalizes":[153],"algorithm":[156],"form.":[159],"Our":[160],"experimental":[161],"text":[164],"three":[167],"typical":[168],"benchmark":[169],"collections":[171],"confirmed":[172],"outperformed":[177],"framework":[180],"settings.":[185]},"counts_by_year":[{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
