{"id":"https://openalex.org/W2072918779","doi":"https://doi.org/10.1145/2487575.2487612","title":"Multi-source deep learning for information trustworthiness estimation","display_name":"Multi-source deep learning for information trustworthiness estimation","publication_year":2013,"publication_date":"2013-08-11","ids":{"openalex":"https://openalex.org/W2072918779","doi":"https://doi.org/10.1145/2487575.2487612","mag":"2072918779"},"language":"en","primary_location":{"id":"doi:10.1145/2487575.2487612","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2487575.2487612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5069736915","display_name":"Liang Ge","orcid":"https://orcid.org/0000-0001-5136-8081"},"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":"Liang Ge","raw_affiliation_strings":["The State University of New York at Buffalo, Buffalo, New York, USA","The State University of New York at Buffalo, Buffalo, New York, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State University of New York at Buffalo, Buffalo, New York, USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"The State University of New York at Buffalo, Buffalo, New York, USA#TAB#","institution_ids":["https://openalex.org/I63190737"]}]},{"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":["The State University of New York at Buffalo, Buffalo, New York, USA","The State University of New York at Buffalo, Buffalo, New York, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State University of New York at Buffalo, Buffalo, New York, USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"The State University of New York at Buffalo, Buffalo, New York, USA#TAB#","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100713499","display_name":"LI Xiao-yi","orcid":"https://orcid.org/0000-0002-5560-3795"},"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":"Xiaoyi Li","raw_affiliation_strings":["The State University of New York at Buffalo, Buffalo, New York, USA","The State University of New York at Buffalo, Buffalo, New York, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State University of New York at Buffalo, Buffalo, New York, USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"The State University of New York at Buffalo, Buffalo, New York, USA#TAB#","institution_ids":["https://openalex.org/I63190737"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013588572","display_name":"Aidong Zhang","orcid":"https://orcid.org/0000-0001-9723-3246"},"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":"Aidong Zhang","raw_affiliation_strings":["The State University of New York at Buffalo, Buffalo, New York, USA","The State University of New York at Buffalo, Buffalo, New York, USA#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The State University of New York at Buffalo, Buffalo, New York, USA","institution_ids":["https://openalex.org/I63190737"]},{"raw_affiliation_string":"The State University of New York at Buffalo, Buffalo, New York, USA#TAB#","institution_ids":["https://openalex.org/I63190737"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I63190737"],"apc_list":null,"apc_paid":null,"fwci":3.2715,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":{"value":0.93115877,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"766","last_page":"774"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9998999834060669,"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":0.9998999834060669,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9990000128746033,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.8035471439361572},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7646545171737671},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5914520025253296},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5811761021614075},{"id":"https://openalex.org/keywords/trustworthiness","display_name":"Trustworthiness","score":0.5751338601112366},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4915548264980316},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4596017003059387},{"id":"https://openalex.org/keywords/latent-variable","display_name":"Latent variable","score":0.4199448227882385},{"id":"https://openalex.org/keywords/information-source","display_name":"Information source (mathematics)","score":0.41888749599456787},{"id":"https://openalex.org/keywords/data-consistency","display_name":"Data consistency","score":0.41292011737823486},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.38749247789382935},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2866339087486267},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.269347220659256},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.13805046677589417},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08842748403549194},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.08428263664245605}],"concepts":[{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.8035471439361572},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7646545171737671},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5914520025253296},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5811761021614075},{"id":"https://openalex.org/C153701036","wikidata":"https://www.wikidata.org/wiki/Q659974","display_name":"Trustworthiness","level":2,"score":0.5751338601112366},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4915548264980316},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4596017003059387},{"id":"https://openalex.org/C51167844","wikidata":"https://www.wikidata.org/wiki/Q4422623","display_name":"Latent variable","level":2,"score":0.4199448227882385},{"id":"https://openalex.org/C2778095710","wikidata":"https://www.wikidata.org/wiki/Q6031225","display_name":"Information source (mathematics)","level":2,"score":0.41888749599456787},{"id":"https://openalex.org/C93361087","wikidata":"https://www.wikidata.org/wiki/Q4426698","display_name":"Data consistency","level":2,"score":0.41292011737823486},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38749247789382935},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2866339087486267},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.269347220659256},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.13805046677589417},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08842748403549194},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.08428263664245605},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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":2,"locations":[{"id":"doi:10.1145/2487575.2487612","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2487575.2487612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.720.9652","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.720.9652","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.buffalo.edu/%7Ejing/doc/kdd13_trustworthiness.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","score":0.4000000059604645,"id":"https://metadata.un.org/sdg/17"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W44815768","https://openalex.org/W107297539","https://openalex.org/W154472438","https://openalex.org/W1515966130","https://openalex.org/W1521736627","https://openalex.org/W1996802155","https://openalex.org/W2020367605","https://openalex.org/W2047756776","https://openalex.org/W2072128103","https://openalex.org/W2072651985","https://openalex.org/W2099866409","https://openalex.org/W2100002341","https://openalex.org/W2100235918","https://openalex.org/W2108502868","https://openalex.org/W2116064496","https://openalex.org/W2118388899","https://openalex.org/W2136922672","https://openalex.org/W2148123869","https://openalex.org/W2159359879","https://openalex.org/W2164587673","https://openalex.org/W2184188583","https://openalex.org/W2294688454","https://openalex.org/W2597289420","https://openalex.org/W2604272474","https://openalex.org/W4231109964","https://openalex.org/W4393032029","https://openalex.org/W6686207219"],"related_works":["https://openalex.org/W2353865532","https://openalex.org/W3010469175","https://openalex.org/W4247233603","https://openalex.org/W2390190248","https://openalex.org/W2048053751","https://openalex.org/W2024918697","https://openalex.org/W2560607624","https://openalex.org/W4294118458","https://openalex.org/W4312532339","https://openalex.org/W127457794"],"abstract_inverted_index":{"In":[0,18],"recent":[1],"years,":[2],"information":[3,16,28,51,78,89,123,172],"trustworthiness":[4,29],"has":[5],"become":[6],"a":[7,41,166,176,194,213],"serious":[8],"issue":[9],"when":[10,152],"user-generated":[11],"contents":[12],"prevail":[13],"in":[14,97,135,206,249],"our":[15],"world.":[17],"this":[19,67],"paper,":[20],"we":[21,69,84,164],"investigate":[22],"the":[23,31,44,57,104,129,159,202,224,229,247,260,265],"important":[24],"problem":[25],"of":[26,33,50,88,119,178,186],"estimating":[27],"from":[30,79,91,158,228,240],"perspective":[32],"correlating":[34],"and":[35,102,121,144,210,243,252,270],"comparing":[36,220],"multiple":[37,80,92,142,184],"data":[38,81,226],"sources.":[39,82],"To":[40],"certain":[42],"extent,":[43],"consistency":[45,173,214],"degree":[46],"is":[47,59,112],"an":[48,71,148],"indicator":[49],"reliability--Information":[52],"unanimously":[53],"agreed":[54],"by":[55,141,183,219],"all":[56,246],"sources":[58,222],"more":[60],"likely":[61],"to":[62,75,170,200],"be":[63,125],"reliable.":[64],"Based":[65],"on":[66,188,235,245],"principle,":[68],"develop":[70],"effective":[72],"computational":[73],"approach":[74,262],"identify":[76,201],"consistent":[77],"Particularly,":[83],"analyze":[85],"vast":[86],"amounts":[87],"collected":[90,239],"review":[93,103],"platforms":[94,115],"(multiple":[95],"sources)":[96],"which":[98,180],"people":[99],"can":[100],"rate":[101],"items":[105,179],"they":[106],"have":[107],"purchased.":[108],"The":[109],"major":[110],"challenge":[111],"that":[113,259,267],"different":[114,189],"attract":[116],"diverse":[117],"sets":[118,185],"users,":[120],"thus":[122,145],"cannot":[124],"compared":[126],"directly":[127],"at":[128],"surface.":[130],"However,":[131],"latent":[132,161,230],"reasons":[133,204],"hidden":[134,205],"user":[136,237],"ratings":[137,156,238],"are":[138,181],"mostly":[139],"shared":[140],"sources,":[143],"inconsistency":[146],"about":[147],"item":[149,218],"only":[150],"appears":[151],"some":[153],"source":[154],"provides":[155],"deviating":[157],"common":[160,203],"reasons.":[162,231],"Therefore,":[163],"propose":[165],"novel":[167],"two-step":[168],"procedure":[169],"calculate":[171,212],"degrees":[174],"for":[175,216],"set":[177],"rated":[182],"users":[187],"platforms.":[190],"We":[191,232],"first":[192],"build":[193],"Multi-Source":[195],"Deep":[196],"Belief":[197],"Network":[198],"(MSDBN)":[199],"multi-source":[207],"rating":[208],"data,":[209],"then":[211],"score":[215],"each":[217],"individual":[221],"with":[223],"reconstructed":[225],"derived":[227],"conduct":[233],"experiments":[234],"real":[236],"Orbitz,":[241],"Priceline":[242],"TripAdvisor":[244],"hotels":[248,266],"Las":[250],"Vegas":[251],"New":[253],"York":[254],"City.":[255],"Experimental":[256],"results":[257],"demonstrate":[258],"proposed":[261],"successfully":[263],"finds":[264],"receive":[268],"inconsistent,":[269],"possibly":[271],"unreliable,":[272],"ratings.":[273]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":8},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}