{"id":"https://openalex.org/W2964301473","doi":"https://doi.org/10.24963/ijcai.2018/534","title":"Weakly Learning to Match Experts in Online Community","display_name":"Weakly Learning to Match Experts in Online Community","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2964301473","doi":"https://doi.org/10.24963/ijcai.2018/534","mag":"2964301473"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2018/534","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/534","pdf_url":"https://www.ijcai.org/proceedings/2018/0534.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2018/0534.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101546902","display_name":"Yujie Qian","orcid":"https://orcid.org/0000-0003-3747-4552"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]},{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["CN","US"],"is_corresponding":true,"raw_author_name":"Yujie Qian","raw_affiliation_strings":["Massachusetts Institute of Technology","Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Massachusetts Institute of Technology","institution_ids":["https://openalex.org/I63966007"]},{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044791875","display_name":"Jie Tang","orcid":"https://orcid.org/0000-0003-3487-4593"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Tang","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101675206","display_name":"Kan Wu","orcid":"https://orcid.org/0000-0002-0663-3410"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kan Wu","raw_affiliation_strings":["Tsinghua University"],"affiliations":[{"raw_affiliation_string":"Tsinghua University","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101546902"],"corresponding_institution_ids":["https://openalex.org/I63966007","https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":3.2894,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.93995831,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"3841","last_page":"3847"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13274","display_name":"Expert finding and Q&A systems","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13274","display_name":"Expert finding and Q&A systems","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/T10028","display_name":"Topic Modeling","score":0.970300018787384,"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":0.7957454919815063},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6922693252563477},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5722596645355225},{"id":"https://openalex.org/keywords/identity","display_name":"Identity (music)","score":0.4783068001270294},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46415361762046814},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4044325649738312},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.39862316846847534},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3807106018066406},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.14455366134643555},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09330826997756958}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7957454919815063},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6922693252563477},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5722596645355225},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.4783068001270294},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46415361762046814},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4044325649738312},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.39862316846847534},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3807106018066406},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.14455366134643555},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09330826997756958},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2018/534","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/534","pdf_url":"https://www.ijcai.org/proceedings/2018/0534.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2018/534","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2018/534","pdf_url":"https://www.ijcai.org/proceedings/2018/0534.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G2674840903","display_name":null,"funder_award_id":"Fellowship","funder_id":"https://openalex.org/F4320320006","funder_display_name":"Royal Society"},{"id":"https://openalex.org/G4155018083","display_name":null,"funder_award_id":"Newton","funder_id":"https://openalex.org/F4320320006","funder_display_name":"Royal Society"},{"id":"https://openalex.org/G5171771356","display_name":null,"funder_award_id":"2014CB","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320320006","display_name":"Royal Society","ror":"https://ror.org/03wnrjx87"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2964301473.pdf","grobid_xml":"https://content.openalex.org/works/W2964301473.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W658020064","https://openalex.org/W1552060966","https://openalex.org/W1558315818","https://openalex.org/W1799750435","https://openalex.org/W1880262756","https://openalex.org/W2000389083","https://openalex.org/W2012435098","https://openalex.org/W2017082987","https://openalex.org/W2064890829","https://openalex.org/W2074275752","https://openalex.org/W2075883161","https://openalex.org/W2078784669","https://openalex.org/W2079665167","https://openalex.org/W2098678088","https://openalex.org/W2099708568","https://openalex.org/W2104973501","https://openalex.org/W2109244020","https://openalex.org/W2131744502","https://openalex.org/W2137813581","https://openalex.org/W2139951984","https://openalex.org/W2167052341","https://openalex.org/W2329863645","https://openalex.org/W2417608402","https://openalex.org/W2513577401","https://openalex.org/W2616814706","https://openalex.org/W2916612367","https://openalex.org/W4240913316","https://openalex.org/W4241676240","https://openalex.org/W4252076394","https://openalex.org/W4294170691"],"related_works":["https://openalex.org/W1972035260","https://openalex.org/W4301594054","https://openalex.org/W2794488505","https://openalex.org/W2961085424","https://openalex.org/W3125889879","https://openalex.org/W3124422538","https://openalex.org/W2295467472","https://openalex.org/W3046451053","https://openalex.org/W2097909533","https://openalex.org/W2502309190"],"abstract_inverted_index":{"In":[0,66],"online":[1,172],"question-and-answer":[2],"(QA)":[3],"websites":[4],"like":[5],"Quora,":[6],"one":[7],"central":[8],"issue":[9],"is":[10,41,106],"to":[11,18,21,33,36,43,83,108,138,174],"find":[12],"(invite)":[13],"users":[14,162],"who":[15],"are":[16],"able":[17],"provide":[19],"answers":[20],"a":[22,76,110,115],"given":[23],"question":[24,54],"and":[25,52,56,74,96,136],"at":[26],"the":[27,37,46,53,57,63,72,85,100,125,140,148,157,177,180],"same":[28],"time":[29],"would":[30],"be":[31],"unlikely":[32],"say":[34],"\"no\"":[35],"invitation.":[38],"The":[39,87],"challenge":[40],"how":[42],"trade":[44],"off":[45],"matching":[47,92,161],"degree":[48,93],"between":[49,94],"users\u2019":[50],"expertise":[51,91],"topic,":[55],"likelihood":[58,101],"of":[59,117,133,179],"positive":[60],"response":[61],"from":[62],"invited":[64,104],"users.":[65,97],"this":[67],"paper,":[68],"we":[69,113],"formally":[70],"formulate":[71],"problem":[73],"develop":[75],"weakly":[77],"supervised":[78],"factor":[79],"graph":[80],"(WeakFG)":[81],"model":[82,88,99,150],"address":[84],"problem.":[86],"explicitly":[89],"captures":[90],"questions":[95],"To":[98],"that":[102,147],"an":[103,171],"user":[105],"willing":[107],"answer":[109],"specific":[111],"question,":[112],"incorporate":[114],"set":[116],"correlations":[118],"based":[119],"on":[120],"social":[121],"identity":[122],"theory":[123],"into":[124],"WeakFG":[126],"model.":[127,142],"We":[128,167],"use":[129],"two":[130],"different":[131],"genres":[132],"datasets:":[134],"QA-Expert":[135],"Paper-Reviewer,":[137],"validate":[139],"proposed":[141,149,181],"Our":[143],"experimental":[144],"results":[145],"show":[146],"can":[151],"significantly":[152],"outperform":[153],"(+1.5-10.7%":[154],"by":[155],"MAP)":[156],"state-of-the-art":[158],"algorithms":[159],"for":[160],"(experts)":[163],"with":[164],"community":[165],"questions.":[166],"have":[168],"also":[169],"developed":[170],"system":[173],"further":[175],"demonstrate":[176],"advantages":[178],"method.":[182]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":4}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}