{"id":"https://openalex.org/W4284706735","doi":"https://doi.org/10.1145/3477495.3531934","title":"Alleviating Spurious Correlations in Knowledge-aware Recommendations through Counterfactual Generator","display_name":"Alleviating Spurious Correlations in Knowledge-aware Recommendations through Counterfactual Generator","publication_year":2022,"publication_date":"2022-07-06","ids":{"openalex":"https://openalex.org/W4284706735","doi":"https://doi.org/10.1145/3477495.3531934"},"language":"en","primary_location":{"id":"doi:10.1145/3477495.3531934","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477495.3531934","pdf_url":null,"source":{"id":"https://openalex.org/S4363608773","display_name":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","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/A5008399761","display_name":"Shanlei Mu","orcid":"https://orcid.org/0000-0002-7795-0579"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanlei Mu","raw_affiliation_strings":["Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046576694","display_name":"Yaliang Li","orcid":"https://orcid.org/0000-0002-4204-6096"},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yaliang Li","raw_affiliation_strings":["Alibaba Group, Bellevue, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba Group, Bellevue, WA, USA","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I4210108985"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037145565","display_name":"Wayne Xin Zhao","orcid":"https://orcid.org/0000-0002-8333-6196"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wayne Xin Zhao","raw_affiliation_strings":["Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100400846","display_name":"Jingyuan Wang","orcid":"https://orcid.org/0000-0003-0651-1592"},"institutions":[{"id":"https://openalex.org/I4210136793","display_name":"Peng Cheng Laboratory","ror":"https://ror.org/03qdqbt06","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210136793"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingyuan Wang","raw_affiliation_strings":["Peng Cheng Laboratory, Shenzhen, Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peng Cheng Laboratory, Shenzhen, Shenzhen, China","institution_ids":["https://openalex.org/I4210136793"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107914397","display_name":"Bolin Ding","orcid":null},"institutions":[{"id":"https://openalex.org/I4210095624","display_name":"Alibaba Group (United States)","ror":"https://ror.org/00rn0m335","country_code":"US","type":"company","lineage":["https://openalex.org/I4210095624","https://openalex.org/I45928872"]},{"id":"https://openalex.org/I4210108985","display_name":"Bellevue Hospital Center","ror":"https://ror.org/01ky34z31","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1283621791","https://openalex.org/I4210086933","https://openalex.org/I4210108985"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bolin Ding","raw_affiliation_strings":["Alibaba Group, Bellevue, WA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alibaba Group, Bellevue, WA, USA","institution_ids":["https://openalex.org/I4210095624","https://openalex.org/I4210108985"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025631695","display_name":"Ji-Rong Wen","orcid":"https://orcid.org/0000-0002-9777-9676"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji-Rong Wen","raw_affiliation_strings":["Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Renmin University of China & Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.2671,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.96732392,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1401","last_page":"1411"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","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/T10203","display_name":"Recommender Systems and Techniques","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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9973999857902527,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.9888252019882202},{"id":"https://openalex.org/keywords/spurious-relationship","display_name":"Spurious relationship","score":0.9441227316856384},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.8144806027412415},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.747041642665863},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5673767328262329},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5459413528442383},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4570924639701843},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33826667070388794},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.08254602551460266}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9888252019882202},{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.9441227316856384},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8144806027412415},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.747041642665863},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5673767328262329},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5459413528442383},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4570924639701843},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33826667070388794},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.08254602551460266},{"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/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3477495.3531934","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3477495.3531934","pdf_url":null,"source":{"id":"https://openalex.org/S4363608773","display_name":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W2102035799","https://openalex.org/W2118795000","https://openalex.org/W2143117649","https://openalex.org/W2143891888","https://openalex.org/W2171279286","https://openalex.org/W2295739661","https://openalex.org/W2419128894","https://openalex.org/W2486285194","https://openalex.org/W2605350416","https://openalex.org/W2759136286","https://openalex.org/W2792839191","https://openalex.org/W2801992635","https://openalex.org/W2883722483","https://openalex.org/W2905569957","https://openalex.org/W2916106175","https://openalex.org/W2945623882","https://openalex.org/W2950275995","https://openalex.org/W2955421345","https://openalex.org/W2963911286","https://openalex.org/W3011809564","https://openalex.org/W3029587262","https://openalex.org/W3035422656","https://openalex.org/W3035512383","https://openalex.org/W3035566692","https://openalex.org/W3035762155","https://openalex.org/W3043411673","https://openalex.org/W3045200674","https://openalex.org/W3088299704","https://openalex.org/W3098087397","https://openalex.org/W3106445281","https://openalex.org/W3129482887","https://openalex.org/W3152876231","https://openalex.org/W3153754021","https://openalex.org/W3154419237","https://openalex.org/W3155919942","https://openalex.org/W3198272940","https://openalex.org/W3199916614","https://openalex.org/W4214717370","https://openalex.org/W6760001035","https://openalex.org/W6779928312"],"related_works":["https://openalex.org/W3201448254","https://openalex.org/W4286970243","https://openalex.org/W2066431708","https://openalex.org/W3113091479","https://openalex.org/W4384133558","https://openalex.org/W2162899405","https://openalex.org/W3025615835","https://openalex.org/W173210993","https://openalex.org/W2390660599","https://openalex.org/W4284706735"],"abstract_inverted_index":{"Limited":[0],"by":[1,33,169],"the":[2,29,34,54,88,100,123,126,140,144,147,150,163,166],"statistical-based":[3],"machine":[4],"learning":[5],"framework,":[6],"a":[7,22,47,59,73,116,173],"spurious":[8,56,132,152],"correlation":[9],"is":[10,37,90,181],"likely":[11],"to":[12,21,28,50,80,98],"appear":[13],"in":[14,39,115],"existing":[15],"knowledge-aware":[16],"recommendation":[17],"methods.":[18],"It":[19],"refers":[20],"knowledge":[23],"fact":[24],"that":[25],"appears":[26],"causal":[27],"user":[30],"behaviors":[31],"(inferred":[32],"recommender)":[35],"but":[36],"not":[38],"fact.":[40],"For":[41],"tackling":[42],"this":[43,121],"issue,":[44],"we":[45],"present":[46],"novel":[48],"approach":[49,66,168],"discovering":[51],"and":[52,72,104,111,134],"alleviating":[53],"potential":[55,131,151],"correlations":[57,133,153],"from":[58,102],"counterfactual":[60,70,76,82,109,127,137,141],"perspective.":[61],"To":[62],"be":[63],"specific,":[64],"our":[65],"consists":[67],"of":[68,149,165,175],"two":[69,93],"generators":[71,77,110,128,142],"recommender.":[74],"The":[75,108],"are":[78,113],"designed":[79],"generate":[81,135],"interactions":[83,106],"via":[84],"reinforcement":[85],"learning,":[86],"while":[87,139],"recommender":[89,112,124,145],"implemented":[91],"with":[92,172],"different":[94],"graph":[95],"neural":[96],"networks":[97],"aggregate":[99],"information":[101],"KG":[103],"user-item":[105],"respectively.":[107],"integrated":[114],"mutually":[117],"collaborative":[118],"way.":[119],"With":[120],"approach,":[122],"helps":[125],"better":[129],"identify":[130],"high-quality":[136],"interactions,":[138],"help":[143],"weaken":[146],"influence":[148],"simultaneously.":[154],"Extensive":[155],"experiments":[156],"on":[157],"three":[158],"real-world":[159],"datasets":[160],"have":[161],"shown":[162],"effectiveness":[164],"proposed":[167],"comparing":[170],"it":[171],"number":[174],"competitive":[176],"baselines.":[177],"Our":[178],"implementation":[179],"code":[180],"available":[182],"at:":[183],"https://github.com/RUCAIBox/CGKR.":[184]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":5}],"updated_date":"2026-08-14T07:06:38.338062","created_date":"2025-10-10T00:00:00"}