{"id":"https://openalex.org/W4394734565","doi":"https://doi.org/10.1145/3657302","title":"LMACL: Improving Graph Collaborative Filtering with Learnable Model Augmentation Contrastive Learning","display_name":"LMACL: Improving Graph Collaborative Filtering with Learnable Model Augmentation Contrastive Learning","publication_year":2024,"publication_date":"2024-04-12","ids":{"openalex":"https://openalex.org/W4394734565","doi":"https://doi.org/10.1145/3657302"},"language":"en","primary_location":{"id":"doi:10.1145/3657302","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3657302","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3657302","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3657302","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101834654","display_name":"Xinru Liu","orcid":"https://orcid.org/0009-0003-0190-6066"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinru Liu","raw_affiliation_strings":["Soochow University, Suzhou, China","School of Computer Science and Technology, Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0009-0003-0190-6066","affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]},{"raw_affiliation_string":"School of Computer Science and Technology, Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100732972","display_name":"Yongjing Hao","orcid":"https://orcid.org/0000-0001-5063-7307"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongjing Hao","raw_affiliation_strings":["Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5063-7307","affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070439966","display_name":"Lei Zhao","orcid":"https://orcid.org/0000-0002-5123-9279"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Zhao","raw_affiliation_strings":["Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-5123-9279","affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070515519","display_name":"Guanfeng Liu","orcid":"https://orcid.org/0000-0001-8980-4950"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Guanfeng Liu","raw_affiliation_strings":["Macquarie University, Sydney, Australia"],"raw_orcid":"https://orcid.org/0000-0001-8980-4950","affiliations":[{"raw_affiliation_string":"Macquarie University, Sydney, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051706630","display_name":"Victor S. Sheng","orcid":"https://orcid.org/0000-0003-4960-174X"},"institutions":[{"id":"https://openalex.org/I12315562","display_name":"Texas Tech University","ror":"https://ror.org/0405mnx93","country_code":"US","type":"education","lineage":["https://openalex.org/I12315562"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Victor S. Sheng","raw_affiliation_strings":["Texas Tech University, Lubbock United States"],"raw_orcid":"https://orcid.org/0000-0003-4960-174X","affiliations":[{"raw_affiliation_string":"Texas Tech University, Lubbock United States","institution_ids":["https://openalex.org/I12315562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016091616","display_name":"Pengpeng Zhao","orcid":"https://orcid.org/0000-0001-6721-6576"},"institutions":[{"id":"https://openalex.org/I3923682","display_name":"Soochow University","ror":"https://ror.org/05t8y2r12","country_code":"CN","type":"education","lineage":["https://openalex.org/I3923682"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengpeng Zhao","raw_affiliation_strings":["Soochow University, Suzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6721-6576","affiliations":[{"raw_affiliation_string":"Soochow University, Suzhou, China","institution_ids":["https://openalex.org/I3923682"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.3933,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.96326485,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"18","issue":"7","first_page":"1","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.984000027179718,"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/T11478","display_name":"Caching and Content Delivery","score":0.9416000247001648,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.8069459199905396},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.6930172443389893},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.6210988759994507},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.45213738083839417},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.44099369645118713},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4386412501335144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.43343478441238403},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38537126779556274},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.3657723665237427}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8069459199905396},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.6930172443389893},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.6210988759994507},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.45213738083839417},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.44099369645118713},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4386412501335144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.43343478441238403},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38537126779556274},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.3657723665237427},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3657302","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3657302","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3657302","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3657302","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3657302","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3657302","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.5199999809265137}],"awards":[{"id":"https://openalex.org/G2891303054","display_name":null,"funder_award_id":"62176175","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4875783979","display_name":null,"funder_award_id":"61876117","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6346158222","display_name":null,"funder_award_id":"62376180","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"},{"id":"https://openalex.org/F4320321605","display_name":"Government of Jiangsu Province","ror":"https://ror.org/004svx814"},{"id":"https://openalex.org/F4320327518","display_name":"Priority Academic Program Development of Jiangsu Higher Education Institutions","ror":null}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4394734565.pdf","grobid_xml":"https://content.openalex.org/works/W4394734565.grobid-xml"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W1720514416","https://openalex.org/W1875842236","https://openalex.org/W2038585576","https://openalex.org/W2054141820","https://openalex.org/W2127345773","https://openalex.org/W2140310134","https://openalex.org/W2187089797","https://openalex.org/W2384310603","https://openalex.org/W2519887557","https://openalex.org/W2741249238","https://openalex.org/W2906413107","https://openalex.org/W2908404712","https://openalex.org/W2945623882","https://openalex.org/W2945827670","https://openalex.org/W2963367478","https://openalex.org/W2964015378","https://openalex.org/W2986515219","https://openalex.org/W2998431760","https://openalex.org/W3003372423","https://openalex.org/W3044311607","https://openalex.org/W3045200674","https://openalex.org/W3065542300","https://openalex.org/W3080525460","https://openalex.org/W3082034060","https://openalex.org/W3093922720","https://openalex.org/W3094127838","https://openalex.org/W3094605801","https://openalex.org/W3100260481","https://openalex.org/W3100278010","https://openalex.org/W3100324210","https://openalex.org/W3129178271","https://openalex.org/W3139159537","https://openalex.org/W3153325943","https://openalex.org/W3156476916","https://openalex.org/W3173365306","https://openalex.org/W3176294187","https://openalex.org/W3187232099","https://openalex.org/W3210938103","https://openalex.org/W3214743507","https://openalex.org/W4224983022","https://openalex.org/W4225412853","https://openalex.org/W4226065821","https://openalex.org/W4289433255","https://openalex.org/W4297733535","https://openalex.org/W4297808394","https://openalex.org/W4307885312","https://openalex.org/W4313598258","https://openalex.org/W4319315274","https://openalex.org/W4321277058","https://openalex.org/W4365794673","https://openalex.org/W4372279027","https://openalex.org/W4379539462","https://openalex.org/W4382203390","https://openalex.org/W4383604692","https://openalex.org/W4384652641","https://openalex.org/W6679197216","https://openalex.org/W6757586295","https://openalex.org/W6853319224"],"related_works":["https://openalex.org/W2772628444","https://openalex.org/W2735929803","https://openalex.org/W4220714703","https://openalex.org/W1484355083","https://openalex.org/W3008845055","https://openalex.org/W2098758514","https://openalex.org/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W2508671622","https://openalex.org/W2556532874"],"abstract_inverted_index":{"Graph":[0],"collaborative":[1,104,111,185],"filtering":[2,112],"(GCF)":[3],"has":[4,22],"achieved":[5],"exciting":[6],"recommendation":[7,76],"performance":[8],"with":[9],"its":[10],"ability":[11],"to":[12,27,45,67,74,106,128,163],"aggregate":[13],"high-order":[14,140],"graph":[15,120,154],"structure":[16],"information.":[17],"Recently,":[18],"contrastive":[19,47,71],"learning":[20,172],"(CL)":[21],"been":[23],"incorporated":[24],"into":[25,132],"GCF":[26],"alleviate":[28],"data":[29],"sparsity":[30],"and":[31,55,102,184,189,216,220],"noise":[32],"issues.":[33],"However,":[34],"most":[35],"of":[36,110,187,214],"the":[37,52,57,69,108,119,139,147,152,174,181,209],"existing":[38],"methods":[39],"employ":[40],"random":[41],"or":[42],"manual":[43],"augmentation":[44,64,160],"produce":[46,68],"views":[48],"that":[49,62,202],"may":[50],"destroy":[51],"original":[53,134],"topology":[54],"amplify":[56],"noisy":[58],"effects.":[59],"We":[60],"argue":[61],"such":[63],"is":[65,227],"insufficient":[66],"optimal":[70],"view,":[72],"leading":[73],"suboptimal":[75],"results.":[77],"In":[78,178],"this":[79,179],"article,":[80],"we":[81,116,150],"proposed":[82],"a":[83,125,205],"L":[84,92],"earnable":[85],"M":[86],"odel":[87],"A":[88],"ugmentation":[89],"C":[90],"ontrastive":[91],"earning":[93],"(LMACL)":[94],"framework":[95],"for":[96],"recommendation,":[97],"which":[98],"effectively":[99],"combines":[100],"graph-level":[101,133],"node-level":[103,167],"relations":[105],"enhance":[107],"expressiveness":[109],"(CF)":[113],"paradigm.":[114],"Specifically,":[115],"first":[117],"use":[118],"convolution":[121],"network":[122,156],"(GCN)":[123],"as":[124,158],"backbone":[126],"encoder":[127],"incorporate":[129],"multi-hop":[130],"neighbors":[131],"node":[135],"representations":[136],"by":[137,218],"leveraging":[138],"connectivity":[141],"in":[142,212],"user-item":[143],"interaction":[144],"graphs.":[145],"At":[146],"same":[148],"time,":[149],"treat":[151],"multi-head":[153],"attention":[155],"(GAT)":[157],"an":[159],"view":[161],"generator":[162],"adaptively":[164],"generate":[165],"high-quality":[166],"augmented":[168],"views.":[169],"Finally,":[170],"joint":[171],"endows":[173],"end-to-end":[175],"training":[176],"fashion.":[177],"case,":[180],"mutual":[182],"supervision":[183],"cooperation":[186],"GCN":[188],"GAT":[190],"achieves":[191],"learnable":[192],"model":[193,224],"augmentation.":[194],"Extensive":[195],"experiments":[196],"on":[197],"several":[198],"benchmark":[199],"datasets":[200],"demonstrate":[201],"LMACL":[203],"provides":[204],"significant":[206],"improvement":[207],"over":[208],"strongest":[210],"baseline":[211],"terms":[213],"Recall":[215],"NDCG":[217],"2.5%\u20133.8%":[219],"1.6%\u20134.0%,":[221],"respectively.":[222],"Our":[223],"implementation":[225],"code":[226],"available":[228],"at":[229],"https://github.com/LiuHsinx/LMACL":[230],".":[231]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":3}],"updated_date":"2026-08-12T21:12:35.861297","created_date":"2025-10-10T00:00:00"}
