{"id":"https://openalex.org/W4321480047","doi":"https://doi.org/10.1145/3539597.3570483","title":"Knowledge-Adaptive Contrastive Learning for Recommendation","display_name":"Knowledge-Adaptive Contrastive Learning for Recommendation","publication_year":2023,"publication_date":"2023-02-22","ids":{"openalex":"https://openalex.org/W4321480047","doi":"https://doi.org/10.1145/3539597.3570483"},"language":"en","primary_location":{"id":"doi:10.1145/3539597.3570483","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539597.3570483","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","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/A5064826982","display_name":"Hao Wang","orcid":"https://orcid.org/0000-0002-9125-7535"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Wang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9125-7535","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072316323","display_name":"Yao Xu","orcid":"https://orcid.org/0000-0002-4748-8133"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao Xu","raw_affiliation_strings":["Researcher, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4748-8133","affiliations":[{"raw_affiliation_string":"Researcher, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060417049","display_name":"Cheng Yang","orcid":"https://orcid.org/0000-0001-7821-0030"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Yang","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7821-0030","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100705849","display_name":"Chuan Shi","orcid":"https://orcid.org/0000-0002-3734-0266"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuan Shi","raw_affiliation_strings":["Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3734-0266","affiliations":[{"raw_affiliation_string":"Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100353721","display_name":"Xin Li","orcid":"https://orcid.org/0000-0001-6888-7064"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xin Li","raw_affiliation_strings":["Researcher, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-6888-7064","affiliations":[{"raw_affiliation_string":"Researcher, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020113235","display_name":"Ning Guo","orcid":"https://orcid.org/0000-0003-2292-432X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ning Guo","raw_affiliation_strings":["Researcher, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2292-432X","affiliations":[{"raw_affiliation_string":"Researcher, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100320723","display_name":"Zhiyuan Liu","orcid":"https://orcid.org/0000-0002-7709-2543"},"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":"Zhiyuan Liu","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7709-2543","affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":36.4313,"has_fulltext":false,"cited_by_count":85,"citation_normalized_percentile":{"value":0.99808682,"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":"535","last_page":"543"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9973000288009644,"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/T10028","display_name":"Topic Modeling","score":0.9692000150680542,"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/computer-science","display_name":"Computer science","score":0.8174352645874023},{"id":"https://openalex.org/keywords/information-overload","display_name":"Information overload","score":0.7791354656219482},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6842759251594543},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.6263047456741333},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5097481608390808},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.500591516494751},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48787856101989746},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4835045635700226},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.46924591064453125},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1751675009727478},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.10590210556983948}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8174352645874023},{"id":"https://openalex.org/C186625053","wikidata":"https://www.wikidata.org/wiki/Q1130191","display_name":"Information overload","level":2,"score":0.7791354656219482},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6842759251594543},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.6263047456741333},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5097481608390808},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.500591516494751},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48787856101989746},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4835045635700226},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.46924591064453125},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1751675009727478},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.10590210556983948},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3539597.3570483","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3539597.3570483","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7437889446","display_name":null,"funder_award_id":"U20B2045,62192784,62172052,62002029,62006129","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W2054141820","https://openalex.org/W2105862907","https://openalex.org/W2509893387","https://openalex.org/W2512971201","https://openalex.org/W2605350416","https://openalex.org/W2792839191","https://openalex.org/W2884134047","https://openalex.org/W2911778742","https://openalex.org/W2913560138","https://openalex.org/W2945623882","https://openalex.org/W2945827670","https://openalex.org/W2963869731","https://openalex.org/W2963911286","https://openalex.org/W2966349618","https://openalex.org/W3011809564","https://openalex.org/W3034364571","https://openalex.org/W3045200674","https://openalex.org/W3094605801","https://openalex.org/W3098087397","https://openalex.org/W3100278010","https://openalex.org/W3106439716","https://openalex.org/W3106445281","https://openalex.org/W3113410469","https://openalex.org/W3129482887","https://openalex.org/W3153325943","https://openalex.org/W3155496675","https://openalex.org/W3155919942","https://openalex.org/W3193441787","https://openalex.org/W3197287220","https://openalex.org/W3207257408","https://openalex.org/W3210938103","https://openalex.org/W4284666445","https://openalex.org/W4292950683"],"related_works":["https://openalex.org/W4251329182","https://openalex.org/W1599110641","https://openalex.org/W1549403601","https://openalex.org/W2497510784","https://openalex.org/W4252183363","https://openalex.org/W2787177576","https://openalex.org/W2078352417","https://openalex.org/W2418053903","https://openalex.org/W2098758514","https://openalex.org/W1575740715"],"abstract_inverted_index":{"By":[0],"jointly":[1],"modeling":[2],"user-item":[3,65,143],"interactions":[4],"and":[5,21,72,92,146,150,196],"knowledge":[6,203],"graph":[7,26],"(KG)":[8],"information,":[9,91],"KG-based":[10,35],"recommender":[11],"systems":[12],"have":[13,30,54],"shown":[14],"their":[15],"superiority":[16],"in":[17,34,81,117],"alleviating":[18,176],"data":[19,140,194],"sparsity":[20],"cold":[22],"start":[23],"problems.":[24],"Recently,":[25],"neural":[27],"networks":[28],"(GNNs)":[29],"been":[31],"widely":[32],"used":[33],"recommendation,":[36],"owing":[37],"to":[38,110,132,168,188],"the":[39,55,61,69,74,99,113,155,165,177,199,217],"strong":[40],"ability":[41],"of":[42,64,76,102,160],"capturing":[43],"high-order":[44],"structural":[45],"information.":[46],"However,":[47],"we":[48,122,137,182],"argue":[49],"that":[50,212],"existing":[51,108],"GNN-based":[52],"methods":[53,109],"following":[56],"two":[57,156,184],"limitations.":[58],"Interaction":[59],"domination:":[60],"supervision":[62],"signal":[63],"interaction":[66,144,178],"will":[67,163],"dominate":[68],"model":[70],"training,":[71],"thus":[73],"information":[75,115,170],"KG":[77,87,147],"is":[78],"barely":[79],"encoded":[80],"learned":[82],"item":[83,166],"representations;":[84],"Knowledge":[85],"overload:":[86],"contains":[88],"much":[89],"recommendation-irrelevant":[90],"such":[93],"noise":[94],"would":[95],"be":[96],"enlarged":[97],"during":[98,193],"message":[100],"aggregation":[101],"GNNs.":[103],"The":[104],"above":[105],"limitations":[106],"prevent":[107],"fully":[111],"utilize":[112],"valuable":[114],"lying":[116],"KG.":[118],"In":[119],"this":[120],"paper,":[121],"propose":[123],"a":[124],"novel":[125],"algorithm":[126],"named":[127],"Knowledge-Adaptive":[128],"Contrastive":[129],"Learning":[130],"(KACL)":[131],"address":[133],"these":[134],"challenges.":[135],"Specifically,":[136],"first":[138],"generate":[139],"augmentations":[141],"from":[142],"view":[145,148,186],"separately,":[149],"perform":[151],"contrastive":[152,161],"learning":[153],"across":[154],"views.":[157],"Our":[158],"design":[159],"loss":[162],"force":[164],"representations":[167],"encode":[169],"shared":[171],"by":[172,202],"both":[173],"views,":[174],"thereby":[175],"domination":[179],"issue.":[180],"Moreover,":[181],"introduce":[183],"learnable":[185],"generators":[187],"adaptively":[189],"remove":[190],"task-irrelevant":[191],"edges":[192],"augmentation,":[195],"help":[197],"tolerate":[198],"noises":[200],"brought":[201],"overload.":[204],"Experimental":[205],"results":[206],"on":[207,219],"three":[208],"public":[209],"benchmarks":[210],"demonstrate":[211],"KACL":[213],"can":[214],"significantly":[215],"improve":[216],"performance":[218],"top-K":[220],"recommendation":[221],"compared":[222],"with":[223],"state-of-the-art":[224],"methods.":[225]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":42},{"year":2024,"cited_by_count":28},{"year":2023,"cited_by_count":8}],"updated_date":"2026-06-20T22:02:38.213706","created_date":"2025-10-10T00:00:00"}
