{"id":"https://openalex.org/W2212248191","doi":"https://doi.org/10.1109/bigdata.2015.7363827","title":"Robust crowd bias correction via dual knowledge transfer from multiple overlapping sources","display_name":"Robust crowd bias correction via dual knowledge transfer from multiple overlapping sources","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2212248191","doi":"https://doi.org/10.1109/bigdata.2015.7363827","mag":"2212248191"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2015.7363827","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2015.7363827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-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/A5102861459","display_name":"Sihong Xie","orcid":"https://orcid.org/0000-0001-5741-9740"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sihong Xie","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055773458","display_name":"Qingbo Hu","orcid":null},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qingbo Hu","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100639603","display_name":"Jingyuan Zhang","orcid":"https://orcid.org/0000-0001-9581-1807"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingyuan Zhang","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100781385","display_name":"Jing Gao","orcid":"https://orcid.org/0000-0001-5099-6991"},"institutions":[{"id":"https://openalex.org/I63190737","display_name":"University at Buffalo, State University of New York","ror":"https://ror.org/01y64my43","country_code":"US","type":"education","lineage":["https://openalex.org/I63190737"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jing Gao","raw_affiliation_strings":["Department of Computer Science, University at Buffalo, Buffalo, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University at Buffalo, Buffalo, NY, USA","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074354165","display_name":"Wei Fan","orcid":"https://orcid.org/0000-0001-9815-710X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wei Fan","raw_affiliation_strings":["Baidu Research Big Data Lab, Sunnyvale, CA, USA"],"affiliations":[{"raw_affiliation_string":"Baidu Research Big Data Lab, Sunnyvale, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036357902","display_name":"Philip S. Yu","orcid":"https://orcid.org/0000-0002-3491-5968"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip S. Yu","raw_affiliation_strings":["Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Illinois at Chicago, Chicago, IL, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5102861459"],"corresponding_institution_ids":["https://openalex.org/I39422238"],"apc_list":null,"apc_paid":null,"fwci":5.5622,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.958999,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"815","last_page":"820"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","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/T11644","display_name":"Spam and Phishing Detection","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":0.9995999932289124,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9979000091552734,"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":0.7856916785240173},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6230239272117615},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.5135672092437744},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.5076965093612671},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5017445087432861},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.4687725901603699},{"id":"https://openalex.org/keywords/crowdsourcing","display_name":"Crowdsourcing","score":0.46667802333831787},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4629918038845062},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.46034717559814453},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.45151379704475403},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4421713948249817},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.4362450838088989},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.43128499388694763},{"id":"https://openalex.org/keywords/strengths-and-weaknesses","display_name":"Strengths and weaknesses","score":0.4104239344596863},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3665645122528076},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.30622851848602295},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.1422918438911438},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.10439595580101013}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7856916785240173},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6230239272117615},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.5135672092437744},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.5076965093612671},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5017445087432861},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.4687725901603699},{"id":"https://openalex.org/C62230096","wikidata":"https://www.wikidata.org/wiki/Q275969","display_name":"Crowdsourcing","level":2,"score":0.46667802333831787},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4629918038845062},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.46034717559814453},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.45151379704475403},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4421713948249817},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.4362450838088989},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.43128499388694763},{"id":"https://openalex.org/C63882131","wikidata":"https://www.wikidata.org/wiki/Q17122954","display_name":"Strengths and weaknesses","level":2,"score":0.4104239344596863},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3665645122528076},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.30622851848602295},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.1422918438911438},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.10439595580101013},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C124952713","wikidata":"https://www.wikidata.org/wiki/Q8242","display_name":"Literature","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2015.7363827","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2015.7363827","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W60106149","https://openalex.org/W1495762646","https://openalex.org/W1975948899","https://openalex.org/W1985514943","https://openalex.org/W2013929512","https://openalex.org/W2022710553","https://openalex.org/W2047756776","https://openalex.org/W2051834357","https://openalex.org/W2067812998","https://openalex.org/W2081988714","https://openalex.org/W2090201253","https://openalex.org/W2090790997","https://openalex.org/W2100119435","https://openalex.org/W2103063352","https://openalex.org/W2132300069","https://openalex.org/W2141519985","https://openalex.org/W2150281577","https://openalex.org/W2159359879","https://openalex.org/W2398879410","https://openalex.org/W2763110165","https://openalex.org/W3122054972","https://openalex.org/W4241168393"],"related_works":["https://openalex.org/W3127142483","https://openalex.org/W4385565564","https://openalex.org/W2898073868","https://openalex.org/W2138488530","https://openalex.org/W2971071571","https://openalex.org/W2798835721","https://openalex.org/W2387658907","https://openalex.org/W2922169395","https://openalex.org/W25098770","https://openalex.org/W2385796165"],"abstract_inverted_index":{"One":[0],"of":[1,5,19,62,115,128,186],"the":[2,9,85,93,98,113,126,156,159,182,201,232,243],"largest":[3],"constituents":[4],"big":[6,129],"data":[7,13,130,161],"is":[8],"crowdsourced":[10,148],"or":[11],"user-generated":[12],"which":[14,138],"contain":[15],"a":[16,38,133,209],"wide":[17],"range":[18],"valuable":[20],"information.":[21],"However,":[22],"they":[23],"are":[24,163],"inherently":[25,165],"biased":[26,48,175],"and":[27,59,89,131,149,173,180,184,215,245],"possibly":[28],"spammed,":[29],"making":[30],"trustworthy":[31,140],"information":[32],"extraction":[33],"an":[34],"imperative":[35],"task.":[36],"As":[37],"special":[39],"case,":[40],"we":[41],"study":[42],"reviewer-posted":[43],"ratings":[44,49,83,87],"for":[45,211],"products.":[46],"The":[47],"can":[50,118,235,246],"lead":[51],"to":[52,56,80,96,199],"disappointed":[53],"customers":[54],"due":[55],"overrated":[57],"products,":[58],"reduced":[60],"revenues":[61],"business":[63],"owners":[64],"caused":[65],"by":[66,176,204],"undeserved":[67],"negative":[68],"ratings.":[69,101],"To":[70],"distill":[71],"objective":[72],"product":[73],"quality":[74],"measurements,":[75],"most":[76,169],"existing":[77],"methods":[78],"try":[79],"infer":[81],"unbiased":[82],"from":[84,151],"raw":[86],"alone,":[88],"may":[90],"not":[91],"overcome":[92],"inherent":[94],"bias":[95,104,217,239],"recover":[97],"underlying":[99],"true":[100],"Though":[102],"improved":[103],"corrections":[105],"have":[106],"been":[107],"achieved":[108],"with":[109,146],"domain":[110,143],"expert":[111,116],"helps,":[112],"overhead":[114],"efforts":[117],"be":[119],"rather":[120],"expensive":[121],"in":[122,218],"practice.":[123],"We":[124,154,178,191],"exploit":[125],"variety":[127],"adopt":[132],"multiple":[134,160],"source":[135],"mining":[136],"approach,":[137],"finds":[139],"measurements":[141],"without":[142],"expert,":[144],"but":[145],"knowledge":[147,188],"transferred":[150],"external":[152],"domains.":[153],"address":[155],"challenges":[157,203],"that":[158,231],"sources":[162,220],"1)":[164],"heterogeneous,":[166],"2)":[167],"at":[168],"only":[170],"partially":[171],"overlapping":[172],"3)":[174],"themselves.":[177],"explore":[179],"analyze":[181],"strengths":[183],"weaknesses":[185],"various":[187],"transfer":[189],"strategies.":[190],"then":[192],"propose":[193],"Consensus":[194],"Ranking":[195],"Dual":[196],"Transfer":[197],"(CRDT)":[198],"handle":[200],"above":[202],"identifying":[205],"\"anchor":[206],"reviewers\"":[207],"as":[208],"bridge":[210],"robust":[212,238],"\"dual":[213],"transfer\",":[214],"removing":[216],"individual":[219],"via":[221],"consensus":[222],"ranking":[223],"aggregation.":[224],"Experiments":[225],"on":[226],"real-world":[227],"rating":[228],"datasets":[229],"demonstrate":[230],"proposed":[233],"approach":[234],"deliver":[236],"more":[237],"correcting":[240],"effects":[241],"than":[242],"baselines":[244],"identify":[247],"abnormal":[248],"reviewers.":[249]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
