{"id":"https://openalex.org/W2998826047","doi":"https://doi.org/10.1109/tnnls.2019.2956523","title":"Robust Cumulative Crowdsourcing Framework Using New Incentive Payment Function and Joint Aggregation Model","display_name":"Robust Cumulative Crowdsourcing Framework Using New Incentive Payment Function and Joint Aggregation Model","publication_year":2020,"publication_date":"2020-01-14","ids":{"openalex":"https://openalex.org/W2998826047","doi":"https://doi.org/10.1109/tnnls.2019.2956523","mag":"2998826047","pmid":"https://pubmed.ncbi.nlm.nih.gov/31945001"},"language":"en","primary_location":{"id":"doi:10.1109/tnnls.2019.2956523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2956523","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5025215650","display_name":"Kamran Ghasedi Dizaji","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Kamran Ghasedi Dizaji","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102798905","display_name":"Hongchang Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hongchang Gao","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I170201317"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035747364","display_name":"Yanhua Yang","orcid":"https://orcid.org/0000-0002-7916-3683"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanhua Yang","raw_affiliation_strings":["Xidian University, Xi\u2019an, China","Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060016795","display_name":"Heng Huang","orcid":"https://orcid.org/0000-0002-3483-8333"},"institutions":[{"id":"https://openalex.org/I170201317","display_name":"University of Pittsburgh","ror":"https://ror.org/01an3r305","country_code":"US","type":"education","lineage":["https://openalex.org/I170201317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Heng Huang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA","JD Finance America Corporation, Mountain View, CA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I170201317"]},{"raw_affiliation_string":"JD Finance America Corporation, Mountain View, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015874725","display_name":"Cheng Deng","orcid":"https://orcid.org/0000-0003-2620-3247"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Deng","raw_affiliation_strings":["Xidian University, Xi\u2019an, China","Xidian University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"Xidian University, Xi\u2019an, China","institution_ids":["https://openalex.org/I149594827"]},{"raw_affiliation_string":"Xidian University, Xi'an, China","institution_ids":["https://openalex.org/I149594827"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5025215650"],"corresponding_institution_ids":["https://openalex.org/I170201317"],"apc_list":null,"apc_paid":null,"fwci":0.5089,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.71934266,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"31","issue":"11","first_page":"4610","last_page":"4621"},"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":0.9912999868392944,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9887999892234802,"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":0.9603579640388489},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7230377793312073},{"id":"https://openalex.org/keywords/payment","display_name":"Payment","score":0.6662747859954834},{"id":"https://openalex.org/keywords/incentive","display_name":"Incentive","score":0.6382026672363281},{"id":"https://openalex.org/keywords/voting","display_name":"Voting","score":0.5618969202041626},{"id":"https://openalex.org/keywords/majority-rule","display_name":"Majority rule","score":0.5340745449066162},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.4947158992290497},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4888591170310974},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4219297766685486},{"id":"https://openalex.org/keywords/data-aggregator","display_name":"Data aggregator","score":0.418677419424057},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3973141312599182},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3595898747444153},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09430238604545593},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.08518823981285095}],"concepts":[{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.9603579640388489},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7230377793312073},{"id":"https://openalex.org/C145097563","wikidata":"https://www.wikidata.org/wiki/Q1148747","display_name":"Payment","level":2,"score":0.6662747859954834},{"id":"https://openalex.org/C29122968","wikidata":"https://www.wikidata.org/wiki/Q1414816","display_name":"Incentive","level":2,"score":0.6382026672363281},{"id":"https://openalex.org/C520049643","wikidata":"https://www.wikidata.org/wiki/Q189760","display_name":"Voting","level":3,"score":0.5618969202041626},{"id":"https://openalex.org/C153668964","wikidata":"https://www.wikidata.org/wiki/Q27636","display_name":"Majority rule","level":2,"score":0.5340745449066162},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.4947158992290497},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4888591170310974},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4219297766685486},{"id":"https://openalex.org/C82578977","wikidata":"https://www.wikidata.org/wiki/Q16773055","display_name":"Data aggregator","level":3,"score":0.418677419424057},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3973141312599182},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3595898747444153},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09430238604545593},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.08518823981285095},{"id":"https://openalex.org/C175444787","wikidata":"https://www.wikidata.org/wiki/Q39072","display_name":"Microeconomics","level":1,"score":0.0},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tnnls.2019.2956523","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tnnls.2019.2956523","pdf_url":null,"source":{"id":"https://openalex.org/S4210175523","display_name":"IEEE Transactions on Neural Networks and Learning Systems","issn_l":"2162-237X","issn":["2162-237X","2162-2388"],"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 Neural Networks and Learning Systems","raw_type":"journal-article"},{"id":"pmid:31945001","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31945001","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on neural networks and learning systems","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.47999998927116394}],"awards":[{"id":"https://openalex.org/G1461465359","display_name":null,"funder_award_id":"61703327","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6777872865","display_name":null,"funder_award_id":"61572388","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":68,"referenced_works":["https://openalex.org/W9014458","https://openalex.org/W140309561","https://openalex.org/W630242894","https://openalex.org/W831822886","https://openalex.org/W1541075651","https://openalex.org/W1543648998","https://openalex.org/W1570705485","https://openalex.org/W1814633089","https://openalex.org/W1879921948","https://openalex.org/W1968166401","https://openalex.org/W1970381522","https://openalex.org/W2025720061","https://openalex.org/W2029343680","https://openalex.org/W2076924522","https://openalex.org/W2108598243","https://openalex.org/W2109062107","https://openalex.org/W2109304399","https://openalex.org/W2115394472","https://openalex.org/W2117130368","https://openalex.org/W2128475742","https://openalex.org/W2134305421","https://openalex.org/W2135029798","https://openalex.org/W2142518823","https://openalex.org/W2146928171","https://openalex.org/W2152009989","https://openalex.org/W2160815625","https://openalex.org/W2163605009","https://openalex.org/W2171849160","https://openalex.org/W2187291759","https://openalex.org/W2187444452","https://openalex.org/W2216621827","https://openalex.org/W2219308446","https://openalex.org/W2293283314","https://openalex.org/W2296319761","https://openalex.org/W2728944333","https://openalex.org/W2783405047","https://openalex.org/W2788352357","https://openalex.org/W2808834459","https://openalex.org/W2892055372","https://openalex.org/W2948398419","https://openalex.org/W2952598059","https://openalex.org/W3121850723","https://openalex.org/W3125666186","https://openalex.org/W3128226684","https://openalex.org/W3141595720","https://openalex.org/W3143596294","https://openalex.org/W4250589301","https://openalex.org/W6619990258","https://openalex.org/W6632436798","https://openalex.org/W6634275384","https://openalex.org/W6638380517","https://openalex.org/W6638392223","https://openalex.org/W6638921482","https://openalex.org/W6639287736","https://openalex.org/W6642336482","https://openalex.org/W6676354425","https://openalex.org/W6679031254","https://openalex.org/W6679959949","https://openalex.org/W6680012447","https://openalex.org/W6680957539","https://openalex.org/W6681455198","https://openalex.org/W6682675497","https://openalex.org/W6684191040","https://openalex.org/W6685032804","https://openalex.org/W6686812563","https://openalex.org/W6686975137","https://openalex.org/W6688494703","https://openalex.org/W6748451695"],"related_works":["https://openalex.org/W3032998312","https://openalex.org/W135177976","https://openalex.org/W4384486036","https://openalex.org/W2039876276","https://openalex.org/W3121841074","https://openalex.org/W2055572829","https://openalex.org/W3036613766","https://openalex.org/W1894159578","https://openalex.org/W2807400035","https://openalex.org/W3125086856"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"crowdsourcing":[3,26,57,217],"has":[4],"gained":[5],"tremendous":[6],"attention":[7],"in":[8,101,220],"the":[9,15,22,87,112,138,174,185,195,205,212],"machine":[10],"learning":[11],"community":[12],"due":[13],"to":[14,94,125,131,136],"increasing":[16,204],"demand":[17],"for":[18,63,98,184,194],"labeled":[19],"data.":[20],"However,":[21],"labels":[23,197],"collected":[24,198],"by":[25,172,199],"are":[27,148,182],"usually":[28],"unreliable":[29],"and":[30,47,153,169,224],"noisy.":[31],"This":[32],"issue":[33],"is":[34,122],"mainly":[35],"caused":[36],"by:":[37],"1)":[38],"nonflexible":[39],"data":[40,82,116,218],"collection":[41,83,117],"mechanisms;":[42],"2)":[43],"nonincentive":[44],"payment":[45,109,120],"functions;":[46],"3)":[48],"inexpert":[49],"crowd":[50,92,129,155,196],"workers.":[51],"We":[52,157],"propose":[53,143],"a":[54,60,79,107,159],"new":[55,80,160],"robust":[56],"framework":[58,70],"as":[59],"comprehensive":[61],"solution":[62],"all":[64],"these":[65],"challenging":[66],"problems.":[67],"Our":[68,207],"unified":[69],"consists":[71],"of":[72,114,222],"three":[73],"novel":[74,108],"components.":[75],"First,":[76],"we":[77,105,142],"introduce":[78],"flexible":[81],"mechanism":[84,202],"based":[85],"on":[86,215],"cumulative":[88],"voting":[89,167],"system,":[90],"allowing":[91],"workers":[93,130],"express":[95],"their":[96,134],"confidence":[97],"each":[99],"option":[100],"multi-choice":[102],"questions.":[103],"Second,":[104],"design":[106],"function":[110,121],"regarding":[111],"settings":[113],"our":[115,200],"mechanism.":[118],"The":[119],"theoretically":[123],"proved":[124],"be":[126],"incentive-compatible,":[127],"encouraging":[128],"disclose":[132],"truthfully":[133],"beliefs":[135],"get":[137],"maximum":[139],"payment.":[140],"Third,":[141],"efficient":[144],"aggregation":[145,161,187,208],"models,":[146],"which":[147],"compatible":[149],"with":[150],"both":[151],"single-option":[152],"multi-option":[154],"labels.":[156],"define":[158],"model,":[162],"called":[163],"simplex":[164],"constrained":[165],"majority":[166],"(SCMV),":[168],"enhance":[170],"it":[171],"using":[173],"probabilistic":[175],"generative":[176],"model.":[177],"Furthermore,":[178],"fast":[179],"optimization":[180],"algorithms":[181],"derived":[183],"proposed":[186,201],"models.":[188],"Experimental":[189],"results":[190],"indicate":[191],"higher":[192],"quality":[193],"without":[203],"cost.":[206],"models":[209,214],"also":[210],"outperform":[211],"state-of-the-art":[213],"multiple":[216],"sets":[219],"terms":[221],"accuracy":[223],"convergence":[225],"speed.":[226]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-03-03T08:47:05.690250","created_date":"2025-10-10T00:00:00"}
