{"id":"https://openalex.org/W3201397997","doi":"https://doi.org/10.1145/3460865","title":"Exploiting Heterogeneous Graph Neural Networks with Latent Worker/Task Correlation Information for Label Aggregation in Crowdsourcing","display_name":"Exploiting Heterogeneous Graph Neural Networks with Latent Worker/Task Correlation Information for Label Aggregation in Crowdsourcing","publication_year":2021,"publication_date":"2021-09-03","ids":{"openalex":"https://openalex.org/W3201397997","doi":"https://doi.org/10.1145/3460865","mag":"3201397997"},"language":"en","primary_location":{"id":"doi:10.1145/3460865","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460865","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","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/A5081343961","display_name":"Hanlu Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanlu Wu","raw_affiliation_strings":["Zhejiang University, Zhejiang, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Zhejiang, P.R.China","institution_ids":["https://openalex.org/I76130692"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086690079","display_name":"Tengfei Ma","orcid":"https://orcid.org/0000-0002-1086-529X"},"institutions":[{"id":"https://openalex.org/I4210114115","display_name":"IBM Research - Thomas J. Watson Research Center","ror":"https://ror.org/0265w5591","country_code":"US","type":"facility","lineage":["https://openalex.org/I1341412227","https://openalex.org/I4210114115"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tengfei Ma","raw_affiliation_strings":["IBM T. J. Watson Research Center, Yorktown Heights, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IBM T. J. Watson Research Center, Yorktown Heights, USA","institution_ids":["https://openalex.org/I4210114115"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011825081","display_name":"Lingfei Wu","orcid":"https://orcid.org/0000-0002-3660-651X"},"institutions":[{"id":"https://openalex.org/I4210086253","display_name":"Silicon Valley Community Foundation","ror":"https://ror.org/001ader08","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210086253"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lingfei Wu","raw_affiliation_strings":["JD.COM Silicon Valley Research Center, Mountain View, CA"],"raw_orcid":"https://orcid.org/0000-0002-3660-651X","affiliations":[{"raw_affiliation_string":"JD.COM Silicon Valley Research Center, Mountain View, CA","institution_ids":["https://openalex.org/I4210086253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046151303","display_name":"Fangli Xu","orcid":"https://orcid.org/0000-0003-1519-2909"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fangli Xu","raw_affiliation_strings":["Squirrel AI Learning"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Squirrel AI Learning","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058611515","display_name":"Shouling Ji","orcid":"https://orcid.org/0000-0003-4268-372X"},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shouling Ji","raw_affiliation_strings":["Zhejiang University, Hangzhou, Zhejiang, P.R.China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University, Hangzhou, Zhejiang, P.R.China","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.0182,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.91855676,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"16","issue":"2","first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":1.0,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9976000189781189,"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/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9886000156402588,"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/crowdsourcing","display_name":"Crowdsourcing","score":0.8249454498291016},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7576709389686584},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.750322163105011},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6219035387039185},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5287753343582153},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4967241883277893},{"id":"https://openalex.org/keywords/homogeneous","display_name":"Homogeneous","score":0.47272104024887085},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4608018696308136},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.2400083839893341},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11120188236236572},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.0836828351020813}],"concepts":[{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.8249454498291016},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7576709389686584},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.750322163105011},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6219035387039185},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5287753343582153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4967241883277893},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.47272104024887085},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4608018696308136},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2400083839893341},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11120188236236572},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0836828351020813},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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":1,"locations":[{"id":"doi:10.1145/3460865","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460865","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","score":0.5,"display_name":"Decent work and economic growth"}],"awards":[{"id":"https://openalex.org/G1280295987","display_name":null,"funder_award_id":"61772466, U1936215, and U1836202","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"},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W9014458","https://openalex.org/W1583837637","https://openalex.org/W1963492191","https://openalex.org/W2056748234","https://openalex.org/W2073068515","https://openalex.org/W2086413055","https://openalex.org/W2093825590","https://openalex.org/W2098865355","https://openalex.org/W2108598243","https://openalex.org/W2113878109","https://openalex.org/W2116341502","https://openalex.org/W2119830539","https://openalex.org/W2141649520","https://openalex.org/W2290431464","https://openalex.org/W2292361954","https://openalex.org/W2296107862","https://openalex.org/W2339885376","https://openalex.org/W2531563875","https://openalex.org/W2561675875","https://openalex.org/W2585105539","https://openalex.org/W2585226541","https://openalex.org/W2602856279","https://openalex.org/W2604738573","https://openalex.org/W2739753637","https://openalex.org/W2786016794","https://openalex.org/W2789042518","https://openalex.org/W2807634467","https://openalex.org/W2897346171","https://openalex.org/W2905224888","https://openalex.org/W2911495555","https://openalex.org/W2912083425","https://openalex.org/W2912269676","https://openalex.org/W2913059114","https://openalex.org/W2913954081","https://openalex.org/W2914304175","https://openalex.org/W2914721378","https://openalex.org/W2915048431","https://openalex.org/W2963091558","https://openalex.org/W2963406064","https://openalex.org/W2963415211","https://openalex.org/W3027664001","https://openalex.org/W3030804940","https://openalex.org/W3115977081","https://openalex.org/W3152893301","https://openalex.org/W4205807230"],"related_works":["https://openalex.org/W3032998312","https://openalex.org/W135177976","https://openalex.org/W4384486036","https://openalex.org/W1503094549","https://openalex.org/W2337920774","https://openalex.org/W4286908577","https://openalex.org/W2886410948","https://openalex.org/W2025875869","https://openalex.org/W4318823662","https://openalex.org/W3207526114"],"abstract_inverted_index":{"Crowdsourcing":[0],"has":[1],"attracted":[2],"much":[3],"attention":[4,106],"for":[5,56],"its":[6],"convenience":[7],"to":[8,19,76],"collect":[9],"labels":[10,40],"from":[11,25,37],"non-expert":[12],"workers":[13,66],"instead":[14],"of":[15,23,80,97],"experts.":[16],"However,":[17],"due":[18],"the":[20,26,34,78,83,89,94,109],"high":[21],"level":[22],"noise":[24],"non-experts,":[27],"a":[28,48,62,71,104],"label":[29,36],"aggregation":[30],"model":[31],"that":[32],"infers":[33],"true":[35,84],"noisy":[38],"crowdsourced":[39],"is":[41],"required.":[42],"In":[43],"this":[44],"article,":[45],"we":[46,87],"propose":[47],"novel":[49],"framework":[50],"based":[51],"on":[52,115],"graph":[53,64,73,110],"neural":[54,74,111],"networks":[55],"aggregating":[57],"crowd":[58],"labels.":[59,85],"We":[60],"construct":[61],"heterogeneous":[63],"between":[65,93],"and":[67,69,82],"tasks":[68],"derive":[70],"new":[72],"network":[75],"learn":[77],"representations":[79],"nodes":[81,98],"Besides,":[86],"exploit":[88],"unknown":[90],"latent":[91],"interaction":[92],"same":[95],"type":[96],"(workers":[99],"or":[100],"tasks)":[101],"by":[102],"adding":[103],"homogeneous":[105],"layer":[107],"in":[108],"networks.":[112],"Experimental":[113],"results":[114],"13":[116],"real-world":[117],"datasets":[118],"show":[119],"superior":[120],"performance":[121],"over":[122],"state-of-the-art":[123],"models.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
