{"id":"https://openalex.org/W3007873369","doi":"https://doi.org/10.1109/bigdata47090.2019.9006319","title":"Uncertainty-Aware Opinion Inference Under Adversarial Attacks","display_name":"Uncertainty-Aware Opinion Inference Under Adversarial Attacks","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3007873369","doi":"https://doi.org/10.1109/bigdata47090.2019.9006319","mag":"3007873369"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata47090.2019.9006319","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006319","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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/A5083827718","display_name":"Adil Alim","orcid":"https://orcid.org/0000-0002-7379-8880"},"institutions":[{"id":"https://openalex.org/I392282","display_name":"University at Albany, State University of New York","ror":"https://ror.org/012zs8222","country_code":"US","type":"education","lineage":["https://openalex.org/I392282"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Adil Alim","raw_affiliation_strings":["Department of Computer Science, University at Albany-SUNY Albany, NY, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University at Albany-SUNY Albany, NY, USA","institution_ids":["https://openalex.org/I392282"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036221931","display_name":"Xujiang Zhao","orcid":"https://orcid.org/0000-0003-4950-4018"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xujiang Zhao","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Dallas, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Dallas, Texas, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011649304","display_name":"Jin-Hee Cho","orcid":"https://orcid.org/0000-0002-5908-4662"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jin-Hee Cho","raw_affiliation_strings":["Department of Computer Science, Vrginia Tech, Falls Church, VA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Vrginia Tech, Falls Church, VA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052987214","display_name":"Feng Chen","orcid":"https://orcid.org/0000-0003-4800-6762"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Feng Chen","raw_affiliation_strings":["Department of Computer Science, The University of Texas at Dallas, Dallas, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Texas at Dallas, Dallas, Texas, USA","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5083827718"],"corresponding_institution_ids":["https://openalex.org/I392282"],"apc_list":null,"apc_paid":null,"fwci":0.5601,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76357365,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"6","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11689","display_name":"Adversarial Robustness in Machine Learning","score":1.0,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9944000244140625,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9922999739646912,"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/adversarial-system","display_name":"Adversarial system","score":0.8994243144989014},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7799299955368042},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7354254722595215},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6946308612823486},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6534925699234009},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5917335748672485},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5714501738548279},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.534630537033081},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.42767447233200073},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.4112612009048462},{"id":"https://openalex.org/keywords/law","display_name":"Law","score":0.09737458825111389}],"concepts":[{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.8994243144989014},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7799299955368042},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7354254722595215},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6946308612823486},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6534925699234009},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5917335748672485},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5714501738548279},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.534630537033081},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.42767447233200073},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.4112612009048462},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.09737458825111389},{"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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata47090.2019.9006319","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata47090.2019.9006319","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.8199999928474426,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W22717428","https://openalex.org/W1561023189","https://openalex.org/W1673923490","https://openalex.org/W1835243625","https://openalex.org/W1991555897","https://openalex.org/W2016707451","https://openalex.org/W2034258124","https://openalex.org/W2110689325","https://openalex.org/W2114094444","https://openalex.org/W2154368244","https://openalex.org/W2164278908","https://openalex.org/W2570685808","https://openalex.org/W2640329709","https://openalex.org/W2782636487","https://openalex.org/W2803831897","https://openalex.org/W2811513716","https://openalex.org/W2907953454","https://openalex.org/W2949103145","https://openalex.org/W2962960408","https://openalex.org/W2963207607","https://openalex.org/W2963389226","https://openalex.org/W2963564844","https://openalex.org/W2964153729","https://openalex.org/W2964283260","https://openalex.org/W3010865323","https://openalex.org/W3098276446","https://openalex.org/W4293846201","https://openalex.org/W6600980184","https://openalex.org/W6637162671","https://openalex.org/W6638588478","https://openalex.org/W6640425456","https://openalex.org/W6682991711","https://openalex.org/W6684379799","https://openalex.org/W6729756640","https://openalex.org/W6731927902","https://openalex.org/W6733049761","https://openalex.org/W6739868092","https://openalex.org/W6749694078","https://openalex.org/W6751569023"],"related_works":["https://openalex.org/W2502115930","https://openalex.org/W2482350142","https://openalex.org/W4246396837","https://openalex.org/W3126451824","https://openalex.org/W1561927205","https://openalex.org/W3191453585","https://openalex.org/W4297672492","https://openalex.org/W4310988119","https://openalex.org/W4285226279","https://openalex.org/W2163814182"],"abstract_inverted_index":{"Inference":[0,49],"of":[1,67,99,117],"unknown":[2,57],"opinions":[3,58],"with":[4,59],"uncertain,":[5,68,103],"adversarial":[6,69,104,130,143],"(e.g.,":[7],"incorrect":[8],"or":[9],"conflicting)":[10],"evidence":[11,70,105],"in":[12,29,154,171],"large":[13],"datasets":[14,153],"is":[15,78,94,107],"not":[16],"a":[17,38,53,97,110],"trivial":[18],"task.":[19],"Without":[20],"proper":[21],"handling,":[22],"it":[23],"can":[24],"easily":[25],"mislead":[26],"decision":[27],"making":[28],"data":[30,137],"mining":[31],"tasks.":[32],"In":[33],"this":[34],"work,":[35],"we":[36],"propose":[37],"highly":[39],"scalable":[40],"opinion":[41],"inference":[42],"probabilistic":[43],"model,":[44],"namely":[45],"Adversarial":[46],"Collective":[47,73],"Opinion":[48],"(Adv-COI),":[50],"which":[51,77,106],"provides":[52],"solution":[54],"to":[55,95,121],"infer":[56],"high":[60],"scalability":[61],"and":[62,83,124,138,140,148,151],"robustness":[63],"under":[64,128,145],"the":[65,92,115,118,133,163,166,172,178],"presence":[66],"by":[71,80],"enhancing":[72],"Subjective":[74],"Logic":[75,86],"(CSL)":[76],"developed":[79],"combining":[81],"SL":[82],"Probabilistic":[84],"Soft":[85],"(PSL).":[87],"The":[88,159],"key":[89],"idea":[90],"behind":[91],"Adv-COI":[93,119,164],"learn":[96],"model":[98],"robust":[100],"ways":[101],"against":[102],"formulated":[108],"as":[109],"min-max":[111],"problem.":[112],"We":[113],"validate":[114],"out-performance":[116],"compared":[120],"baseline":[122],"models":[123],"its":[125],"competitive":[126],"counterparts":[127],"possible":[129],"attacks":[131,144],"on":[132],"logic-rule":[134],"based":[135],"structured":[136],"white":[139],"black":[141],"box":[142],"both":[146],"clean":[147],"perturbed":[149],"semi-synthetic":[150],"real-world":[152],"three":[155],"real":[156],"world":[157],"applications.":[158],"results":[160],"show":[161],"that":[162],"generates":[165],"lowest":[167,179],"mean":[168],"absolute":[169],"error":[170],"expected":[173],"truth":[174],"probability":[175],"while":[176],"producing":[177],"running":[180],"time":[181],"among":[182],"all.":[183]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
