{"id":"https://openalex.org/W2075359503","doi":"https://doi.org/10.1145/1968613.1968619","title":"Initial training data selection for active learning","display_name":"Initial training data selection for active learning","publication_year":2011,"publication_date":"2011-02-21","ids":{"openalex":"https://openalex.org/W2075359503","doi":"https://doi.org/10.1145/1968613.1968619","mag":"2075359503"},"language":"en","primary_location":{"id":"doi:10.1145/1968613.1968619","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1968613.1968619","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication","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/A5101899176","display_name":"Weiwei Yuan","orcid":"https://orcid.org/0000-0002-0452-4536"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Yuan","raw_affiliation_strings":["Harbin Engineering University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102879526","display_name":"Yongkoo Han","orcid":"https://orcid.org/0000-0003-4541-2052"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yongkoo Han","raw_affiliation_strings":["Kyung Hee University, Yongin-Si, Korea","[Kyung Hee University, Yongin-si, Korea]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyung Hee University, Yongin-Si, Korea","institution_ids":["https://openalex.org/I35928602"]},{"raw_affiliation_string":"[Kyung Hee University, Yongin-si, Korea]","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003852858","display_name":"Donghai Guan","orcid":"https://orcid.org/0000-0002-8448-9020"},"institutions":[{"id":"https://openalex.org/I151727225","display_name":"Harbin Engineering University","ror":"https://ror.org/03x80pn82","country_code":"CN","type":"education","lineage":["https://openalex.org/I151727225"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donghai Guan","raw_affiliation_strings":["Harbin Engineering University, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Harbin Engineering University, Harbin, China","institution_ids":["https://openalex.org/I151727225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101882040","display_name":"Sungyoung Lee","orcid":"https://orcid.org/0000-0002-5962-1587"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sungyoung Lee","raw_affiliation_strings":["Kyung Hee University, Yongin-Si, Korea","[Kyung Hee University, Yongin-si, Korea]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyung Hee University, Yongin-Si, Korea","institution_ids":["https://openalex.org/I35928602"]},{"raw_affiliation_string":"[Kyung Hee University, Yongin-si, Korea]","institution_ids":["https://openalex.org/I35928602"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039165136","display_name":"Young-Koo Lee","orcid":"https://orcid.org/0000-0003-2314-5395"},"institutions":[{"id":"https://openalex.org/I35928602","display_name":"Kyung Hee University","ror":"https://ror.org/01zqcg218","country_code":"KR","type":"education","lineage":["https://openalex.org/I35928602"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Young-Koo Lee","raw_affiliation_strings":["Kyung Hee University, Yongin-Si, Korea","[Kyung Hee University, Yongin-si, Korea]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kyung Hee University, Yongin-Si, Korea","institution_ids":["https://openalex.org/I35928602"]},{"raw_affiliation_string":"[Kyung Hee University, Yongin-si, Korea]","institution_ids":["https://openalex.org/I35928602"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6379,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.90737526,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","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/T12072","display_name":"Machine Learning and Algorithms","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/T11550","display_name":"Text and Document Classification Technologies","score":0.9675999879837036,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9650999903678894,"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/selection","display_name":"Selection (genetic algorithm)","score":0.7330386638641357},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7156322598457336},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6621349453926086},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6362282037734985},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5949810743331909},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.567309558391571},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5644731521606445},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.398858904838562}],"concepts":[{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.7330386638641357},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7156322598457336},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6621349453926086},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6362282037734985},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5949810743331909},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.567309558391571},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5644731521606445},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.398858904838562}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1968613.1968619","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1968613.1968619","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Ubiquitous Information Management and Communication","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G207025390","display_name":null,"funder_award_id":"2010-0018941","funder_id":"https://openalex.org/F4320322120","funder_display_name":"National Research Foundation of Korea"}],"funders":[{"id":"https://openalex.org/F4320322120","display_name":"National Research Foundation of Korea","ror":"https://ror.org/013aysd81"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W105263016","https://openalex.org/W1513874326","https://openalex.org/W1553262910","https://openalex.org/W1992419399","https://openalex.org/W2019950953","https://openalex.org/W2085989833","https://openalex.org/W2107502455","https://openalex.org/W2113076747","https://openalex.org/W2114663556","https://openalex.org/W2115305054","https://openalex.org/W2136504847","https://openalex.org/W2151023586","https://openalex.org/W2168822971","https://openalex.org/W2171332245","https://openalex.org/W2914515968","https://openalex.org/W4230588984","https://openalex.org/W6680140577"],"related_works":["https://openalex.org/W4298130764","https://openalex.org/W2044488462","https://openalex.org/W2981877337","https://openalex.org/W3203938600","https://openalex.org/W2169074127","https://openalex.org/W2163707935","https://openalex.org/W83146503","https://openalex.org/W202723009","https://openalex.org/W4206462905","https://openalex.org/W2165396616"],"abstract_inverted_index":{"The":[0,123],"crucial":[1],"issue":[2,31],"in":[3,95],"many":[4],"classification":[5],"applications":[6],"is":[7,25,114],"how":[8],"to":[9],"achieve":[10],"the":[11,34,46,57,88,105,108,115,153],"best":[12],"possible":[13],"classifier":[14],"with":[15,90,142],"a":[16,131],"limited":[17],"number":[18],"of":[19,48,93,117,125,133,155],"labeled":[20],"training":[21,59,69,100,146],"data.":[22,101],"Active":[23],"learning":[24,50],"one":[26],"method":[27],"which":[28],"addresses":[29],"this":[30,41],"by":[32],"selecting":[33,56,144],"most":[35],"informative":[36],"data":[37,70,135],"for":[38],"training.":[39],"In":[40],"work,":[42],"we":[43,65],"argue":[44],"that":[45],"performance":[47,154],"active":[49,156],"could":[51],"be":[52],"improved":[53],"through":[54],"carefully":[55],"initial":[58,68,99,145],"samples.":[60],"To":[61],"confirm":[62],"our":[63],"argument,":[64],"propose":[66],"three":[67],"selection":[71,81,86,103,113,119,149],"mechanisms":[72],"based":[73],"on":[74,130],"fuzzy":[75],"clustering":[76],"method:":[77],"center-based":[78,118],"selection,":[79],"border-based":[80,121],"and":[82,120],"hybrid":[83,148],"selection.":[84,122],"Center-based":[85],"selects":[87,104],"samples":[89,106],"high":[91],"degree":[92],"membership":[94],"each":[96],"cluster":[97],"as":[98],"Border-based":[102],"around":[107],"border":[109],"between":[110],"clusters.":[111],"Hybrid":[112],"combination":[116],"effects":[124],"them":[126],"are":[127],"empirically":[128],"studied":[129],"set":[132],"UCI":[134],"sets.":[136],"Experimental":[137],"result":[138],"indicates":[139],"that,":[140],"compared":[141],"randomly":[143],"samples,":[147],"can":[150],"effectively":[151],"enhance":[152],"learning.":[157]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
