{"id":"https://openalex.org/W2004672916","doi":"https://doi.org/10.1109/tkde.2014.2365785","title":"Active Learning for Ranking through Expected Loss Optimization","display_name":"Active Learning for Ranking through Expected Loss Optimization","publication_year":2014,"publication_date":"2014-10-30","ids":{"openalex":"https://openalex.org/W2004672916","doi":"https://doi.org/10.1109/tkde.2014.2365785","mag":"2004672916"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2014.2365785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2014.2365785","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","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/A5101920986","display_name":"Bo Long","orcid":"https://orcid.org/0000-0001-5129-8546"},"institutions":[{"id":"https://openalex.org/I1316064682","display_name":"LinkedIn (United States)","ror":"https://ror.org/02fyxhe35","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I1316064682"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Bo Long","raw_affiliation_strings":["LinkedIn Inc., Mountain View, CA","LinkedIn Inc., Mountain View, CA#TAB#"],"affiliations":[{"raw_affiliation_string":"LinkedIn Inc., Mountain View, CA","institution_ids":["https://openalex.org/I1316064682"]},{"raw_affiliation_string":"LinkedIn Inc., Mountain View, CA#TAB#","institution_ids":["https://openalex.org/I1316064682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101544241","display_name":"Jiang Bian","orcid":"https://orcid.org/0000-0002-9472-600X"},"institutions":[{"id":"https://openalex.org/I1290206253","display_name":"Microsoft (United States)","ror":"https://ror.org/00d0nc645","country_code":"US","type":"company","lineage":["https://openalex.org/I1290206253"]},{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jiang Bian","raw_affiliation_strings":["Microsoft Research, Beijing, China","Microsoft Research, , Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]},{"raw_affiliation_string":"Microsoft Research, , Beijing, China","institution_ids":["https://openalex.org/I1290206253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075009867","display_name":"Olivier Chapelle","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Olivier Chapelle","raw_affiliation_strings":["Criteo, Palo Alto, CA"],"affiliations":[{"raw_affiliation_string":"Criteo, Palo Alto, CA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100342828","display_name":"Ya Zhang","orcid":"https://orcid.org/0000-0002-5390-9053"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ya Zhang","raw_affiliation_strings":["Shanghai Jiao Tong University, Shanghai, China","[Shanghai Jiao Tong University, Shanghai, China]"],"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"[Shanghai Jiao Tong University, Shanghai, China]","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035179095","display_name":"Yoshiyuki Inagaki","orcid":"https://orcid.org/0000-0001-9275-3314"},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yoshiyuki Inagaki","raw_affiliation_strings":["Yahoo! Labs, Sunnyvale, CA","Yahoo Labs, Sunnyvale, CA"],"affiliations":[{"raw_affiliation_string":"Yahoo! Labs, Sunnyvale, CA","institution_ids":["https://openalex.org/I4210134091"]},{"raw_affiliation_string":"Yahoo Labs, Sunnyvale, CA","institution_ids":["https://openalex.org/I4210134091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029392006","display_name":"Yi Chang","orcid":"https://orcid.org/0000-0003-2697-8093"},"institutions":[{"id":"https://openalex.org/I4210134091","display_name":"Yahoo (United States)","ror":"https://ror.org/040dkzz12","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134091"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yi Chang","raw_affiliation_strings":["Yahoo! Labs, Sunnyvale, CA","Yahoo Labs, Sunnyvale, CA"],"affiliations":[{"raw_affiliation_string":"Yahoo! Labs, Sunnyvale, CA","institution_ids":["https://openalex.org/I4210134091"]},{"raw_affiliation_string":"Yahoo Labs, Sunnyvale, CA","institution_ids":["https://openalex.org/I4210134091"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5101920986"],"corresponding_institution_ids":["https://openalex.org/I1316064682"],"apc_list":null,"apc_paid":null,"fwci":3.6811,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.93495987,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"27","issue":"5","first_page":"1180","last_page":"1191"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","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/T12072","display_name":"Machine Learning and Algorithms","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/T12288","display_name":"Optimization and Search Problems","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.994700014591217,"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":0.8116896152496338},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.805087149143219},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.8021200895309448},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6836792230606079},{"id":"https://openalex.org/keywords/ranking-svm","display_name":"Ranking SVM","score":0.6664251089096069},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.6268110871315002},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5586023330688477},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4792313873767853},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.446713924407959},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4224429726600647},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0821748673915863}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8116896152496338},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.805087149143219},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.8021200895309448},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6836792230606079},{"id":"https://openalex.org/C124975894","wikidata":"https://www.wikidata.org/wiki/Q7293290","display_name":"Ranking SVM","level":3,"score":0.6664251089096069},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.6268110871315002},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5586023330688477},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4792313873767853},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.446713924407959},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4224429726600647},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0821748673915863},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2014.2365785","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2014.2365785","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","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 Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4892476598","display_name":null,"funder_award_id":"61221001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8514106306","display_name":null,"funder_award_id":"61003107","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W42414577","https://openalex.org/W59786464","https://openalex.org/W1483816357","https://openalex.org/W1514707997","https://openalex.org/W1528361845","https://openalex.org/W1531797482","https://openalex.org/W1552767446","https://openalex.org/W1553262910","https://openalex.org/W1678356000","https://openalex.org/W1708221419","https://openalex.org/W1773652845","https://openalex.org/W1974160425","https://openalex.org/W1988520084","https://openalex.org/W2018770010","https://openalex.org/W2031972533","https://openalex.org/W2047221353","https://openalex.org/W2058176813","https://openalex.org/W2068744901","https://openalex.org/W2071643468","https://openalex.org/W2091158010","https://openalex.org/W2093347820","https://openalex.org/W2100235073","https://openalex.org/W2117896839","https://openalex.org/W2124504084","https://openalex.org/W2130492741","https://openalex.org/W2142537246","https://openalex.org/W2143331230","https://openalex.org/W2167432060","https://openalex.org/W2170347328","https://openalex.org/W2400142570","https://openalex.org/W2951911250","https://openalex.org/W3103871524","https://openalex.org/W4285719527","https://openalex.org/W6601679287","https://openalex.org/W6628964739","https://openalex.org/W6630882758","https://openalex.org/W6631818227","https://openalex.org/W6632992187","https://openalex.org/W6637533267","https://openalex.org/W6637954352","https://openalex.org/W6655195918","https://openalex.org/W6675295016"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W2036613096","https://openalex.org/W2138488530","https://openalex.org/W2963493716","https://openalex.org/W2293317945","https://openalex.org/W4318960487","https://openalex.org/W2089835261","https://openalex.org/W1786507113","https://openalex.org/W2621001737","https://openalex.org/W4231380332"],"abstract_inverted_index":{"Learning":[0],"to":[1,16,21,67,85,112,135,178],"rank":[2],"arises":[3],"in":[4,38,76],"many":[5],"data":[6,51,199],"mining":[7],"applications,":[8],"ranging":[9],"from":[10],"web":[11,197],"search":[12,198],"engine,":[13],"online":[14],"advertising":[15],"recommendation":[17],"system.":[18],"In":[19,91],"learning":[20,65,88,99,149],"rank,":[22],"the":[23,33,39,43,63,77,176,181,187,190,208],"performance":[24],"of":[25,35,116,189,207],"a":[26,59,96,113,124,154],"ranking":[27,73,117],"model":[28],"is":[29,52,80,110,173],"strongly":[30],"affected":[31],"by":[32],"number":[34],"labeled":[36,47],"examples":[37,48,71],"training":[40,50],"set;":[41],"on":[42,195],"other":[44],"hand,":[45],"obtaining":[46],"for":[49,62,72,89,105,150,175],"very":[53,82],"expensive":[54],"and":[55,145,152,162,205,211],"time-consuming.":[56],"This":[57],"presents":[58],"great":[60,203],"need":[61],"active":[64,87,98,148,166],"approaches":[66],"select":[68,136],"most":[69,137],"informative":[70,138],"learning;":[74],"however,":[75],"literature":[78],"there":[79],"still":[81],"limited":[83],"work":[84],"address":[86],"ranking.":[90,106],"this":[92,120],"paper,":[93],"we":[94,122,141,169],"propose":[95,153],"general":[97],"framework,":[100,121],"expected":[101,127],"loss":[102,132,191],"optimization":[103,133],"(ELO),":[104],"The":[107],"ELO":[108],"framework":[109,210],"applicable":[111],"wide":[114],"range":[115],"functions.":[118],"Under":[119],"derive":[123],"novel":[125],"algorithm,":[126],"discounted":[128],"cumulative":[129],"gain":[130],"(DCG)":[131],"(ELO-DCG),":[134],"examples.":[139],"Then,":[140],"investigate":[142],"both":[143,160],"query":[144,161],"document":[146,163],"level":[147],"raking":[151],"two-stage":[155],"ELO-DCG":[156],"algorithm":[157,177],"which":[158],"incorporate":[159],"selection":[164],"into":[165],"learning.":[167],"Furthermore,":[168],"show":[170],"that":[171],"it":[172],"flexible":[174],"deal":[179],"with":[180,186],"skewed":[182],"grade":[183],"distribution":[184],"problem":[185],"modification":[188],"function.":[192],"Extensive":[193],"experiments":[194],"real-world":[196],"sets":[200],"have":[201],"demonstrated":[202],"potential":[204],"effectiveness":[206],"proposed":[209],"algorithms.":[212]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":12},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":6},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
