{"id":"https://openalex.org/W4385488564","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191752","title":"MFGCL: Light graph contrast learning with multi-feature information for recommendation","display_name":"MFGCL: Light graph contrast learning with multi-feature information for recommendation","publication_year":2023,"publication_date":"2023-06-18","ids":{"openalex":"https://openalex.org/W4385488564","doi":"https://doi.org/10.1109/ijcnn54540.2023.10191752"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn54540.2023.10191752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","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/A5102207831","display_name":"Yijun Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yijun Zhao","raw_affiliation_strings":["College of Mathematics and Informatics, South China Agricultural University,Guangzhou,China","College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University,Guangzhou,China","institution_ids":["https://openalex.org/I101479585"]},{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046395131","display_name":"Fajian Jiang","orcid":null},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fajian Jiang","raw_affiliation_strings":["College of Mathematics and Informatics, South China Agricultural University,Guangzhou,China","College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University,Guangzhou,China","institution_ids":["https://openalex.org/I101479585"]},{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China","institution_ids":["https://openalex.org/I101479585"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100344675","display_name":"Jinfeng Wang","orcid":"https://orcid.org/0000-0002-1246-4617"},"institutions":[{"id":"https://openalex.org/I101479585","display_name":"South China Agricultural University","ror":"https://ror.org/05v9jqt67","country_code":"CN","type":"education","lineage":["https://openalex.org/I101479585"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinfeng Wang","raw_affiliation_strings":["College of Mathematics and Informatics, South China Agricultural University,Guangzhou,China","College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University,Guangzhou,China","institution_ids":["https://openalex.org/I101479585"]},{"raw_affiliation_string":"College of Mathematics and Informatics, South China Agricultural University, Guangzhou, China","institution_ids":["https://openalex.org/I101479585"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102207831"],"corresponding_institution_ids":["https://openalex.org/I101479585"],"apc_list":null,"apc_paid":null,"fwci":1.8327,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.88253359,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"01","last_page":"08"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9383000135421753,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8684428930282593},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.6261743903160095},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5695796012878418},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.5554271936416626},{"id":"https://openalex.org/keywords/information-overload","display_name":"Information overload","score":0.5397684574127197},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.5287969708442688},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4872971773147583},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4649715721607208},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4460929036140442},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.42964670062065125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4157540798187256},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3820309042930603},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.17746394872665405},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.11850443482398987}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8684428930282593},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.6261743903160095},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5695796012878418},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.5554271936416626},{"id":"https://openalex.org/C186625053","wikidata":"https://www.wikidata.org/wiki/Q1130191","display_name":"Information overload","level":2,"score":0.5397684574127197},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5287969708442688},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4872971773147583},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4649715721607208},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4460929036140442},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.42964670062065125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4157540798187256},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3820309042930603},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.17746394872665405},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.11850443482398987},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn54540.2023.10191752","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn54540.2023.10191752","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2009205701","https://openalex.org/W2048531216","https://openalex.org/W2054141820","https://openalex.org/W2140310134","https://openalex.org/W2152790380","https://openalex.org/W2159094788","https://openalex.org/W2605350416","https://openalex.org/W2741249238","https://openalex.org/W2808561426","https://openalex.org/W2894039884","https://openalex.org/W2945827670","https://openalex.org/W2963146368","https://openalex.org/W3003875435","https://openalex.org/W3045200674","https://openalex.org/W3094605801","https://openalex.org/W3100278010","https://openalex.org/W3114652457","https://openalex.org/W3131393612","https://openalex.org/W3153325943","https://openalex.org/W3154246858","https://openalex.org/W3208338073","https://openalex.org/W4226183797","https://openalex.org/W4297971002","https://openalex.org/W4381786098","https://openalex.org/W4385270524","https://openalex.org/W6680830989","https://openalex.org/W6682948231","https://openalex.org/W6773368452","https://openalex.org/W6810609158","https://openalex.org/W6841186867","https://openalex.org/W6843189178","https://openalex.org/W6917172014"],"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/W4376854386","https://openalex.org/W2202724490","https://openalex.org/W4251329182","https://openalex.org/W1599110641","https://openalex.org/W2098758514"],"abstract_inverted_index":{"Collaborative":[0],"filtering(CF)":[1],"uses":[2],"user":[3,8,41,112,122],"history":[4],"data":[5,50,130,153],"to":[6,24,29,38,125,139,154],"predict":[7],"preferences":[9],"and":[10,53,103,113,147,163,185],"recommend":[11],"items":[12,54,104],"that":[13,63],"users":[14,52,102],"may":[15],"be":[16,36,193],"interested":[17],"in.":[18],"Although":[19],"there":[20],"are":[21],"many":[22],"ways":[23],"use":[25],"graph":[26,79],"convolutional":[27],"networks":[28],"extend":[30],"traditional":[31],"CF,":[32],"effective":[33,149],"information":[34,100,150],"cannot":[35],"used":[37],"fully":[39],"express":[40],"preferences.":[42,123],"At":[43],"the":[44,47,56,65,70,98,108,111,127,155,161,166,175,178,183],"same":[45],"time,":[46],"sparse":[48,152],"interaction":[49,99],"between":[51,101,110],"in":[55],"scenario":[57],"is":[58,137],"also":[59,106],"an":[60],"important":[61],"factors":[62],"affect":[64],"recommendation":[66,84],"effect.":[67],"To":[68],"address":[69],"above":[71],"issues,":[72],"we":[73],"propose":[74],"a":[75,132],"light":[76],"multi-feature":[77],"information-enhanced":[78],"contrastive":[80],"learning":[81,135],"model":[82],"for":[83],"scenarios":[85],"(MFGCL).":[86],"Based":[87],"on":[88,170],"LightGCN,":[89],"when":[90],"propagating":[91],"neighborhood":[92],"information,":[93],"it":[94],"not":[95],"only":[96],"propagates":[97],"but":[105],"learns":[107],"relationship":[109],"item":[114],"features.":[115],"This":[116],"aggregation":[117],"method":[118],"more":[119],"comprehensively":[120],"represents":[121],"Secondly,":[124],"solve":[126],"problem":[128],"of":[129,165,177,187],"sparsity,":[131],"three-channel":[133],"self-supervised":[134],"framework":[136],"constructed":[138],"generate":[140],"comparative":[141],"views":[142],"by":[143],"adding":[144],"uniform":[145],"noise":[146],"extracting":[148],"from":[151],"greatest":[156],"extent,":[157],"which":[158,181],"can":[159,192],"improve":[160],"expressiveness":[162],"scalability":[164],"model.":[167],"Experimental":[168],"results":[169],"three":[171],"public":[172],"datasets":[173],"demonstrate":[174],"effectiveness":[176],"proposed":[179],"method,":[180],"promotes":[182],"precision":[184],"accuracy":[186],"recommendations":[188],"greatly.":[189],"The":[190],"code":[191],"available":[194],"at":[195],"https://github.com/mintZYJ/MFGCL":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}