{"id":"https://openalex.org/W3156622960","doi":"https://doi.org/10.1145/3442381.3449788","title":"Disentangling User Interest and Conformity for Recommendation with Causal Embedding","display_name":"Disentangling User Interest and Conformity for Recommendation with Causal Embedding","publication_year":2021,"publication_date":"2021-04-19","ids":{"openalex":"https://openalex.org/W3156622960","doi":"https://doi.org/10.1145/3442381.3449788","mag":"3156622960"},"language":"en","primary_location":{"id":"doi:10.1145/3442381.3449788","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449788","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3442381.3449788","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100681020","display_name":"Yu Zheng","orcid":"https://orcid.org/0000-0002-1837-6730"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yu Zheng","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology &amp; Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology &amp; Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078622343","display_name":"Chen Gao","orcid":"https://orcid.org/0000-0002-7561-5646"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chen Gao","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology &amp; Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology &amp; Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007642977","display_name":"Xiang Li","orcid":"https://orcid.org/0000-0001-5529-071X"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiang Li","raw_affiliation_strings":["University of Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Hong Kong, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038668215","display_name":"Xiangnan He","orcid":"https://orcid.org/0000-0001-8472-7992"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiangnan He","raw_affiliation_strings":["University of Science and Technology of China, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100355277","display_name":"Yong Li","orcid":"https://orcid.org/0000-0001-5617-1659"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yong Li","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology &amp; Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology &amp; Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044100655","display_name":"Depeng Jin","orcid":"https://orcid.org/0000-0003-0419-5514"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Depeng Jin","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology &amp; Tsinghua University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology &amp; Tsinghua University, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100681020"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":70.5326,"has_fulltext":false,"cited_by_count":325,"citation_normalized_percentile":{"value":0.99963036,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2980","last_page":"2991"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.996399998664856,"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":0.9927999973297119,"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/interpretability","display_name":"Interpretability","score":0.8627893328666687},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.804095447063446},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7584644556045532},{"id":"https://openalex.org/keywords/conformity","display_name":"Conformity","score":0.7017940878868103},{"id":"https://openalex.org/keywords/dice","display_name":"Dice","score":0.6536514759063721},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6199861764907837},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.508358895778656},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.47482308745384216},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.44255179166793823},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4297630786895752},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4040995240211487},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4020887613296509},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09629249572753906}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8627893328666687},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.804095447063446},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7584644556045532},{"id":"https://openalex.org/C142172996","wikidata":"https://www.wikidata.org/wiki/Q221284","display_name":"Conformity","level":2,"score":0.7017940878868103},{"id":"https://openalex.org/C22029948","wikidata":"https://www.wikidata.org/wiki/Q45089","display_name":"Dice","level":2,"score":0.6536514759063721},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6199861764907837},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.508358895778656},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.47482308745384216},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.44255179166793823},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4297630786895752},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4040995240211487},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4020887613296509},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09629249572753906},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","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:10.1145/3442381.3449788","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449788","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3442381.3449788","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449788","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1224564842","https://openalex.org/W2008156638","https://openalex.org/W2023205960","https://openalex.org/W2046974451","https://openalex.org/W2054141820","https://openalex.org/W2187089797","https://openalex.org/W2219888463","https://openalex.org/W2296073425","https://openalex.org/W2507134384","https://openalex.org/W2517898103","https://openalex.org/W2552627818","https://openalex.org/W2624431344","https://openalex.org/W2629213068","https://openalex.org/W2739587313","https://openalex.org/W2740253077","https://openalex.org/W2748058847","https://openalex.org/W2765564115","https://openalex.org/W2784068709","https://openalex.org/W2799048248","https://openalex.org/W2801365175","https://openalex.org/W2807021761","https://openalex.org/W2886453691","https://openalex.org/W2892888989","https://openalex.org/W2913491198","https://openalex.org/W2914052719","https://openalex.org/W2917760808","https://openalex.org/W2945653123","https://openalex.org/W2955421345","https://openalex.org/W2963657860","https://openalex.org/W3009804075","https://openalex.org/W3045200674","https://openalex.org/W3099420497","https://openalex.org/W3100848837","https://openalex.org/W3100945072","https://openalex.org/W3103310105","https://openalex.org/W3106000504","https://openalex.org/W3123384096","https://openalex.org/W3129194741","https://openalex.org/W6703949738"],"related_works":["https://openalex.org/W3104750253","https://openalex.org/W2475857072","https://openalex.org/W2483429559","https://openalex.org/W4366341510","https://openalex.org/W3021239166","https://openalex.org/W2390936256","https://openalex.org/W2016385589","https://openalex.org/W2009559548","https://openalex.org/W2905433371","https://openalex.org/W2906397153"],"abstract_inverted_index":{"Recommendation":[0],"models":[1,106],"are":[2,65,75,81,99],"usually":[3],"trained":[4],"on":[5,156,160],"observational":[6,10],"interaction":[7,11,64],"data.":[8,47],"However,":[9,48],"data":[12,135],"could":[13,107],"result":[14],"from":[15],"users\u2019":[16,23],"conformity":[17,53,98],"towards":[18],"popular":[19],"items,":[20],"which":[21,136],"entangles":[22],"real":[24],"interest.":[25],"Existing":[26],"methods":[27],"tracks":[28],"this":[29,84],"problem":[30],"as":[31,68],"eliminating":[32],"popularity":[33],"bias,":[34],"e.g.,":[35],"by":[36,56,131],"re-weighting":[37],"training":[38,132],"samples":[39],"or":[40],"leveraging":[41],"a":[42,89],"small":[43],"fraction":[44],"of":[45,51,62,144,162,187],"unbiased":[46],"the":[49,141,170,175,183],"variety":[50],"user":[52],"is":[54,137],"ignored":[55],"these":[57],"approaches,":[58],"and":[59,73,97,102,114,121,123,178,185],"different":[60],"causes":[61,80],"an":[63],"bundled":[66],"together":[67],"unified":[69],"representations,":[70],"hence":[71],"robustness":[72,184],"interpretability":[74,186],"not":[76],"guaranteed":[77],"when":[78],"underlying":[79],"changing.":[82],"In":[83],"paper,":[85],"we":[86],"present":[87],"DICE,":[88],"general":[90],"framework":[91],"that":[92,169,180],"learns":[93],"representations":[94],"where":[95],"interest":[96,120],"structurally":[100],"disentangled,":[101],"various":[103,163],"backbone":[104,164],"recommendation":[105],"be":[108],"smoothly":[109],"integrated.":[110],"We":[111,166],"assign":[112],"users":[113],"items":[115],"with":[116,133,153],"separate":[117],"embeddings":[118,172],"for":[119],"conformity,":[122],"make":[124],"each":[125],"embedding":[126],"capture":[127,174],"only":[128],"one":[129],"cause":[130],"cause-specific":[134],"obtained":[138],"according":[139],"to":[140],"colliding":[142],"effect":[143],"causal":[145],"inference.":[146],"Our":[147],"proposed":[148],"methodology":[149],"outperforms":[150],"state-of-the-art":[151],"baselines":[152],"remarkable":[154],"improvements":[155],"two":[157],"real-world":[158],"datasets":[159],"top":[161],"models.":[165],"further":[167],"demonstrate":[168],"learned":[171],"successfully":[173],"desired":[176],"causes,":[177],"show":[179],"DICE":[181],"guarantees":[182],"recommendation.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":68},{"year":2024,"cited_by_count":92},{"year":2023,"cited_by_count":94},{"year":2022,"cited_by_count":51},{"year":2021,"cited_by_count":11}],"updated_date":"2026-05-21T09:19:25.381259","created_date":"2025-10-10T00:00:00"}
