{"id":"https://openalex.org/W2153819437","doi":"https://doi.org/10.1109/tmm.2002.1017738","title":"An active learning framework for content-based information retrieval","display_name":"An active learning framework for content-based information retrieval","publication_year":2002,"publication_date":"2002-06-01","ids":{"openalex":"https://openalex.org/W2153819437","doi":"https://doi.org/10.1109/tmm.2002.1017738","mag":"2153819437"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2002.1017738","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2002.1017738","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","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/A5103551927","display_name":"Cha Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Cha Zhang","raw_affiliation_strings":["Department of Electrical and Engineering, Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Engineering, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000454484","display_name":"Tsuhan Chen","orcid":"https://orcid.org/0000-0003-3951-7931"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tsuhan Chen","raw_affiliation_strings":["Department of Electrical and Engineering, Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Engineering, Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103551927"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":12.7845,"has_fulltext":false,"cited_by_count":204,"citation_normalized_percentile":{"value":0.98884442,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":"4","issue":"2","first_page":"260","last_page":"268"},"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.996399998664856,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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":0.9961000084877014,"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":0.8700343370437622},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5727617144584656},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5528391599655151},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5217845439910889},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5185723900794983},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4953833818435669},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.44913992285728455},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4440917372703552},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.42341774702072144},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3964715600013733},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3836113214492798}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8700343370437622},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5727617144584656},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5528391599655151},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5217845439910889},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5185723900794983},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4953833818435669},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.44913992285728455},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4440917372703552},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.42341774702072144},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3964715600013733},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3836113214492798},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/tmm.2002.1017738","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2002.1017738","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"},{"id":"pmh:oai:scholarbank.nus.edu.sg:10635/146362","is_oa":false,"landing_page_url":"http://scholarbank.nus.edu.sg/handle/10635/146362","pdf_url":null,"source":{"id":"https://openalex.org/S7407052290","display_name":"National University of Singapore","issn_l":null,"issn":[],"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":"Scopus","raw_type":"Article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.10.6852","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.10.6852","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.andrew.cmu.edu/user/czhang/publications/mm02_Cha2.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.12.2380","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.2380","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://amp.ece.cmu.edu/Publication/Cha/mm2002_Cha2.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.9.5083","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.9.5083","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.andrew.cmu.edu/user/czhang/publications/tr01_04.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8299999833106995,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320310207","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1507347479","https://openalex.org/W1514707997","https://openalex.org/W1528361845","https://openalex.org/W1581953323","https://openalex.org/W1601503327","https://openalex.org/W1609461728","https://openalex.org/W1667009210","https://openalex.org/W1938998932","https://openalex.org/W1967904143","https://openalex.org/W1983071923","https://openalex.org/W2000672666","https://openalex.org/W2036421173","https://openalex.org/W2050947749","https://openalex.org/W2065010255","https://openalex.org/W2080021732","https://openalex.org/W2084134149","https://openalex.org/W2085989833","https://openalex.org/W2087499664","https://openalex.org/W2089349283","https://openalex.org/W2099111195","https://openalex.org/W2099396366","https://openalex.org/W2100911004","https://openalex.org/W2101498401","https://openalex.org/W2110327402","https://openalex.org/W2118269922","https://openalex.org/W2128073546","https://openalex.org/W2129905273","https://openalex.org/W2135306884","https://openalex.org/W2139301100","https://openalex.org/W2139399907","https://openalex.org/W2140549709","https://openalex.org/W2146558186","https://openalex.org/W2150411325","https://openalex.org/W2155099190","https://openalex.org/W2161475482","https://openalex.org/W2167725992","https://openalex.org/W2570764145","https://openalex.org/W2949071206","https://openalex.org/W2951911250","https://openalex.org/W3017143921","https://openalex.org/W4233014035","https://openalex.org/W4242599275","https://openalex.org/W6630509579","https://openalex.org/W6636452984","https://openalex.org/W6679154154"],"related_works":["https://openalex.org/W2737719445","https://openalex.org/W3147584709","https://openalex.org/W2977677679","https://openalex.org/W1992327129","https://openalex.org/W2898210368","https://openalex.org/W2381986121","https://openalex.org/W2382480268","https://openalex.org/W2370918718","https://openalex.org/W2256933480","https://openalex.org/W2914897824"],"abstract_inverted_index":{"We":[0,11],"propose":[1],"a":[2,34,161,194],"general":[3],"active":[4,241],"learning":[5,53,103,242,244],"framework":[6,14],"for":[7,164],"content-based":[8],"information":[9],"retrieval.":[10],"use":[12],"this":[13,43],"to":[15,21,63,66,77,117,144,147,166],"guide":[16],"hidden":[17],"annotations":[18],"in":[19,29,57,182],"order":[20],"improve":[22],"the":[23,30,40,48,52,58,64,87,93,102,120,129,132,141,145,155,168,176,183,198,202,223,227,232],"retrieval":[24,224],"performance.":[25],"For":[26,69,95],"each":[27,38,70,73],"object":[28,44,181],"database,":[31],"we":[32,238],"maintain":[33],"list":[35,156],"of":[36,42,47,157,197,217,226,234],"probabilities,":[37],"indicating":[39],"probability":[41,74],"having":[45],"one":[46,79,128],"attributes.":[49,68,152],"During":[50,153],"training,":[51],"algorithm":[54,104,207],"samples":[55],"objects":[56,96,121,190],"database":[59],"and":[60,179,201,214],"presents":[61,138],"them":[62],"annotator":[65,146],"assign":[67],"sampled":[71],"object,":[72],"is":[75,90,114,131,150,191,208],"set":[76],"be":[78],"or":[80,85,174],"zero":[81],"depending":[82],"on":[83,210,246],"whether":[84],"not":[86,99,124],"corresponding":[88],"attribute":[89],"assigned":[91,151],"by":[92,193],"annotator.":[94],"that":[97,122,240],"have":[98,123],"been":[100,125],"annotated,":[101,126],"estimates":[105],"their":[106],"probabilities":[107,158],"with":[108,231],"biased":[109],"kernel":[110],"regression.":[111],"Knowledge":[112],"gain":[113],"then":[115,137],"defined":[116],"determine,":[118],"among":[119],"which":[127,148],"system":[130,136,228],"most":[133],"uncertain.":[134],"The":[135,185,206],"it":[139,149],"as":[140,160],"next":[142],"sample":[143],"retrieval,":[154],"works":[159],"feature":[162,204],"vector":[163],"us":[165],"calculate":[167],"semantic":[169,199],"distance":[170,187,200],"between":[171,175,188],"two":[172,189],"objects,":[173],"user":[177],"query":[178],"an":[180],"database.":[184],"overall":[186],"determined":[192],"weighted":[195],"sum":[196],"low-level":[203],"distance.":[205],"tested":[209],"both":[211,221],"synthetic":[212],"databases":[213,216],"real":[215],"3D":[218],"models.":[219],"In":[220],"cases,":[222],"performance":[225],"improves":[229],"rapidly":[230],"number":[233],"annotated":[235],"samples.":[236],"Furthermore,":[237],"show":[239],"outperforms":[243],"based":[245],"random":[247],"sampling.":[248]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":4},{"year":2013,"cited_by_count":10},{"year":2012,"cited_by_count":18}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}