{"id":"https://openalex.org/W4200101754","doi":"https://doi.org/10.1109/bigmm52142.2021.00019","title":"Counterfactual Embedding Learning for Debiased Recommendation","display_name":"Counterfactual Embedding Learning for Debiased Recommendation","publication_year":2021,"publication_date":"2021-11-01","ids":{"openalex":"https://openalex.org/W4200101754","doi":"https://doi.org/10.1109/bigmm52142.2021.00019"},"language":"en","primary_location":{"id":"doi:10.1109/bigmm52142.2021.00019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigmm52142.2021.00019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Seventh International Conference on Multimedia Big Data (BigMM)","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/A5015870451","display_name":"Meng Jian","orcid":"https://orcid.org/0000-0001-5659-5128"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Meng Jian","raw_affiliation_strings":["Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100764789","display_name":"Jingjing Guo","orcid":"https://orcid.org/0009-0003-9645-2246"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingjing Guo","raw_affiliation_strings":["Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101831667","display_name":"Ye Xiang","orcid":"https://orcid.org/0000-0003-1945-7433"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ye Xiang","raw_affiliation_strings":["Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005945981","display_name":"Lifang Wu","orcid":"https://orcid.org/0000-0002-7209-0215"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lifang Wu","raw_affiliation_strings":["Beijing University of Technology, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology, Beijing, China","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5015870451"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2884667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"69","last_page":"73"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","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/T10203","display_name":"Recommender Systems and Techniques","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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9941999912261963,"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"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.98089998960495,"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/counterfactual-thinking","display_name":"Counterfactual thinking","score":0.9495474696159363},{"id":"https://openalex.org/keywords/debiasing","display_name":"Debiasing","score":0.8831685185432434},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.7925547361373901},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7407866716384888},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7009503841400146},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5200235843658447},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47292453050613403},{"id":"https://openalex.org/keywords/masking","display_name":"Masking (illustration)","score":0.45635417103767395},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.09213832020759583},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.07105612754821777}],"concepts":[{"id":"https://openalex.org/C108650721","wikidata":"https://www.wikidata.org/wiki/Q1783253","display_name":"Counterfactual thinking","level":2,"score":0.9495474696159363},{"id":"https://openalex.org/C2779458634","wikidata":"https://www.wikidata.org/wiki/Q24963715","display_name":"Debiasing","level":2,"score":0.8831685185432434},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.7925547361373901},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7407866716384888},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7009503841400146},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5200235843658447},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47292453050613403},{"id":"https://openalex.org/C2777402240","wikidata":"https://www.wikidata.org/wiki/Q6783436","display_name":"Masking (illustration)","level":2,"score":0.45635417103767395},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.09213832020759583},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.07105612754821777},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigmm52142.2021.00019","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigmm52142.2021.00019","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Seventh International Conference on Multimedia Big Data (BigMM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1992380306","https://openalex.org/W2023603028","https://openalex.org/W2077927809","https://openalex.org/W2124187902","https://openalex.org/W2140310134","https://openalex.org/W2219888463","https://openalex.org/W2318991869","https://openalex.org/W2340502990","https://openalex.org/W2507134384","https://openalex.org/W2543154812","https://openalex.org/W2605350416","https://openalex.org/W2624617553","https://openalex.org/W2629213068","https://openalex.org/W2783279085","https://openalex.org/W2788651580","https://openalex.org/W2892888989","https://openalex.org/W2911286998","https://openalex.org/W2917760808","https://openalex.org/W2962977061","https://openalex.org/W2963331808","https://openalex.org/W2984589663","https://openalex.org/W2998534896","https://openalex.org/W3034203759","https://openalex.org/W3034348890","https://openalex.org/W3035404611","https://openalex.org/W3044963235","https://openalex.org/W3103310105","https://openalex.org/W3104589861","https://openalex.org/W3106000504","https://openalex.org/W3177934633","https://openalex.org/W4293876646","https://openalex.org/W4310228395","https://openalex.org/W6680830989","https://openalex.org/W6695055480","https://openalex.org/W6738844735","https://openalex.org/W6748316862","https://openalex.org/W6779283709","https://openalex.org/W6783775357"],"related_works":["https://openalex.org/W4362554880","https://openalex.org/W4281684980","https://openalex.org/W4386875279","https://openalex.org/W2171721708","https://openalex.org/W4390963114","https://openalex.org/W4287887864","https://openalex.org/W3214527415","https://openalex.org/W1495104519","https://openalex.org/W4225584739","https://openalex.org/W2199432031"],"abstract_inverted_index":{"Recently,":[0],"recommender":[1],"system":[2],"suffers":[3],"extremely":[4],"from":[5],"both":[6],"interaction":[7,22],"bias":[8,71,101],"and":[9,24,30,48,67,76,86,92,99,111,122],"sparsity.":[10],"The":[11],"conventional":[12],"unified":[13],"embedding":[14,42],"learning":[15,43],"policies":[16],"fail":[17],"to":[18,40,73,95,127,147],"consider":[19],"the":[20,35,69,106,136,142],"imbalanced":[21],"issue":[23],"produce":[25],"suboptimal":[26],"representations":[27],"of":[28,59,84,130],"users":[29,75,85],"items":[31,77,87],"for":[32,55],"recommendation.":[33,57],"Towards":[34],"end,":[36],"this":[37],"work":[38],"dedicates":[39],"bias-aware":[41,117],"in":[44],"a":[45,50,79,116],"decomposed":[46],"manner":[47],"proposes":[49],"Counterfactual":[51],"Embedding":[52],"Learning":[53],"(CEL)":[54],"debiased":[56],"Instead":[58],"debiasing":[60],"with":[61,78,90,135],"sampling":[62],"uniform":[63],"interactions,":[64],"we":[65],"follow":[66],"capitalize":[68],"natural":[70],"distribution":[72],"model":[74,96],"counterfactual":[80,118,125],"hypothesis.":[81],"Concretely,":[82],"embeddings":[83],"are":[88],"built":[89],"common":[91,110],"special":[93,112,132],"causes":[94,133],"latent":[97],"frequent":[98],"infrequent":[100],"isometrically.":[102],"Particularly,":[103],"relying":[104],"on":[105,120],"frequency":[107],"gap":[108],"between":[109],"causes,":[113],"CEL":[114,144],"introduces":[115],"masking":[119],"interactions":[121],"forms":[123],"multiple":[124],"worlds":[126],"extract":[128],"effects":[129],"various":[131],"comparing":[134],"factual":[137],"world.":[138],"Experiments":[139],"show":[140],"that":[141],"proposed":[143],"performs":[145],"superior":[146],"state-of-the-art":[148],"baselines.":[149]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}