{"id":"https://openalex.org/W2166686248","doi":"https://doi.org/10.1145/2232817.2232833","title":"Modeling and exploiting heterogeneous bibliographic networks for expertise ranking","display_name":"Modeling and exploiting heterogeneous bibliographic networks for expertise ranking","publication_year":2012,"publication_date":"2012-06-10","ids":{"openalex":"https://openalex.org/W2166686248","doi":"https://doi.org/10.1145/2232817.2232833","mag":"2166686248"},"language":"en","primary_location":{"id":"doi:10.1145/2232817.2232833","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2232817.2232833","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101786215","display_name":"Hongbo Deng","orcid":"https://orcid.org/0000-0002-9659-5111"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongbo Deng","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Urbana, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019539533","display_name":"Jiawei Han","orcid":"https://orcid.org/0000-0002-3629-2696"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jiawei Han","raw_affiliation_strings":["University of Illinois at Urbana-Champaign, Urbana, IL, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Urbana-Champaign, Urbana, IL, USA","institution_ids":["https://openalex.org/I157725225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069596903","display_name":"Michael R. Lyu","orcid":"https://orcid.org/0000-0002-3666-5798"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Michael R. Lyu","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042251906","display_name":"Irwin King","orcid":"https://orcid.org/0000-0001-8106-6447"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Irwin King","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":62,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"71","last_page":"80"},"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":0.992900013923645,"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9894000291824341,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.838884711265564},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7252026200294495},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5741897821426392},{"id":"https://openalex.org/keywords/intuition","display_name":"Intuition","score":0.5618274211883545},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.5173120498657227},{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.4779389202594757},{"id":"https://openalex.org/keywords/publication","display_name":"Publication","score":0.4299558997154236},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.426815927028656},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4060284495353699},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21950608491897583}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.838884711265564},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7252026200294495},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5741897821426392},{"id":"https://openalex.org/C132010649","wikidata":"https://www.wikidata.org/wiki/Q189222","display_name":"Intuition","level":2,"score":0.5618274211883545},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.5173120498657227},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.4779389202594757},{"id":"https://openalex.org/C41458344","wikidata":"https://www.wikidata.org/wiki/Q732577","display_name":"Publication","level":2,"score":0.4299558997154236},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.426815927028656},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4060284495353699},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21950608491897583},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C112698675","wikidata":"https://www.wikidata.org/wiki/Q37038","display_name":"Advertising","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/2232817.2232833","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2232817.2232833","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 12th ACM/IEEE-CS joint conference on Digital Libraries","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.301.1630","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.301.1630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.uiuc.edu/~hanj/pdf/jcdl12_hdong.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.364.9963","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.9963","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.uiuc.edu/~hbdeng/jcdl2012_fp085-deng.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.44999998807907104,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338295","display_name":"Army Research Laboratory","ror":"https://ror.org/011hc8f90"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W38978401","https://openalex.org/W139119103","https://openalex.org/W1970461679","https://openalex.org/W1972594981","https://openalex.org/W2043252224","https://openalex.org/W2064890829","https://openalex.org/W2066636486","https://openalex.org/W2091565080","https://openalex.org/W2093390569","https://openalex.org/W2096738524","https://openalex.org/W2101599977","https://openalex.org/W2104973501","https://openalex.org/W2109244020","https://openalex.org/W2109943925","https://openalex.org/W2110896767","https://openalex.org/W2121392694","https://openalex.org/W2126226055","https://openalex.org/W2126497299","https://openalex.org/W2132613313","https://openalex.org/W2138621811","https://openalex.org/W2139823104","https://openalex.org/W2143561480","https://openalex.org/W2149288670","https://openalex.org/W2150461699","https://openalex.org/W2151122348","https://openalex.org/W2154455818","https://openalex.org/W2157339239","https://openalex.org/W2158201212","https://openalex.org/W2159133636","https://openalex.org/W2162010993","https://openalex.org/W2165611133","https://openalex.org/W3214920796","https://openalex.org/W4206765718","https://openalex.org/W6601604913","https://openalex.org/W6682494755"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W4390446658","https://openalex.org/W2971071571","https://openalex.org/W2798835721","https://openalex.org/W2387658907","https://openalex.org/W2922169395","https://openalex.org/W25098770"],"abstract_inverted_index":{"Recently":[0],"expertise":[1,16,83,132],"retrieval":[2,133],"has":[3],"received":[4],"increasing":[5],"interests":[6],"in":[7,55,62],"both":[8],"academia":[9],"and":[10,36,51,77,175,184,207,227],"industry.":[11],"Finding":[12],"experts":[13],"with":[14,48,104,181,203],"demonstrated":[15],"for":[17,82,172],"a":[18,22,27,126,200],"given":[19],"query":[20],"is":[21],"nontrivial":[23],"task":[24],"especially":[25],"from":[26],"large-scale":[28],"Web":[29],"2.0":[30],"systems,":[31],"such":[32],"as":[33,138],"question":[34],"answering":[35],"bibliography":[37,201],"data,":[38],"where":[39],"users":[40],"are":[41],"actively":[42],"publishing":[43],"useful":[44,81],"content":[45,70],"online,":[46],"interacting":[47],"each":[49],"other,":[50],"forming":[52],"social":[53],"networks":[54,61,137],"various":[56],"ways,":[57],"leading":[58],"to":[59,64,79,130,168,195],"heterogeneous":[60,97,119,136],"addition":[63],"the":[65,92,116,182,193,225],"large":[66],"amounts":[67],"of":[68,87,108,111,118,143],"textual":[69,93],"information.":[71,109,186],"Many":[72],"approaches":[73],"have":[74],"been":[75],"proposed":[76,217],"shown":[78],"be":[80,157],"ranking.":[84],"However,":[85],"most":[86],"these":[88],"methods":[89],"only":[90],"consider":[91],"documents":[94],"while":[95],"ignoring":[96],"network":[98],"structures":[99],"or":[100],"can":[101,113,219],"merely":[102],"integrate":[103],"one":[105],"additional":[106],"kind":[107],"None":[110],"them":[112],"fully":[114],"exploit":[115],"characteristics":[117,171],"networks.":[120],"In":[121],"this":[122,162],"paper,":[123],"we":[124,164,191],"propose":[125],"joint":[127],"regularization":[128,139],"framework":[129,194],"enhance":[131],"by":[134,161],"modeling":[135],"constraints":[140],"on":[141],"top":[142],"document-centric":[144],"model.":[145],"We":[146],"argue":[147],"that":[148,215],"multi-typed":[149],"linking":[150],"edges":[151],"reveal":[152],"valuable":[153],"information":[154],"which":[155],"should":[156],"treated":[158],"differently.":[159],"Motivated":[160],"intuition,":[163],"formulate":[165],"three":[166],"hypotheses":[167,179],"capture":[169],"unique":[170],"different":[173],"graphs,":[174],"mathematically":[176],"model":[177],"those":[178],"jointly":[180],"document":[183],"other":[185,228],"To":[187],"illustrate":[188],"our":[189,216],"methodology,":[190],"apply":[192],"expert":[196],"finding":[197],"applications":[198],"using":[199],"dataset":[202],"1.1":[204],"million":[205,209],"papers":[206],"0.7":[208],"authors.":[210],"The":[211],"experimental":[212],"results":[213,223],"show":[214],"approach":[218],"achieve":[220],"significantly":[221],"better":[222],"than":[224],"baseline":[226],"enhanced":[229],"models.":[230]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":5},{"year":2015,"cited_by_count":7},{"year":2014,"cited_by_count":7},{"year":2013,"cited_by_count":13},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}