{"id":"https://openalex.org/W3184692286","doi":"https://doi.org/10.1109/tkde.2021.3099217","title":"Beyond Similarity: Relation-based Collaborative Filtering","display_name":"Beyond Similarity: Relation-based Collaborative Filtering","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3184692286","doi":"https://doi.org/10.1109/tkde.2021.3099217","mag":"3184692286"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2021.3099217","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3099217","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5100607490","display_name":"Guannan Liu","orcid":"https://orcid.org/0000-0002-4532-7109"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guannan Liu","raw_affiliation_strings":["Department of Information Systems, Beihang University, 12633 Beijing, Beijing, China, 100191 (e-mail: guannliu@gmail.com)"],"affiliations":[{"raw_affiliation_string":"Department of Information Systems, Beihang University, 12633 Beijing, Beijing, China, 100191 (e-mail: guannliu@gmail.com)","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100425225","display_name":"Liang Zhang","orcid":"https://orcid.org/0000-0002-5805-7099"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Liang Zhang","raw_affiliation_strings":["Computer Science, Nanyang Technological University, 54761 Singapore, Singapore, Singapore, (e-mail: LIANG012@e.ntu.edu.sg)"],"affiliations":[{"raw_affiliation_string":"Computer Science, Nanyang Technological University, 54761 Singapore, Singapore, Singapore, (e-mail: LIANG012@e.ntu.edu.sg)","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035293475","display_name":"Junjie Wu","orcid":"https://orcid.org/0000-0001-7650-3657"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junjie Wu","raw_affiliation_strings":["Information Systems, Beihang University, 12633 Beijing, Beijing, China, (e-mail: wujj@buaa.edu.cn)"],"affiliations":[{"raw_affiliation_string":"Information Systems, Beihang University, 12633 Beijing, Beijing, China, (e-mail: wujj@buaa.edu.cn)","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100607490"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":3.5804,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.93533676,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":1.0,"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":1.0,"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":0.9758999943733215,"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/T10609","display_name":"Digital Marketing and Social Media","score":0.9376000165939331,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"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/collaborative-filtering","display_name":"Collaborative filtering","score":0.8010077476501465},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7981191873550415},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.7595900893211365},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.708264946937561},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6924413442611694},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.615610659122467},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5141523480415344},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.47597020864486694},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.47040992975234985},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4418282210826874},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.43447020649909973}],"concepts":[{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.8010077476501465},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7981191873550415},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.7595900893211365},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.708264946937561},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6924413442611694},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.615610659122467},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5141523480415344},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.47597020864486694},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.47040992975234985},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4418282210826874},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.43447020649909973},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2021.3099217","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2021.3099217","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5600000023841858}],"awards":[{"id":"https://openalex.org/G1305972272","display_name":null,"funder_award_id":"71725002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3226113683","display_name":null,"funder_award_id":"71701007","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3695564058","display_name":null,"funder_award_id":"72031001","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5152102630","display_name":null,"funder_award_id":"U1636210","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G5415502266","display_name":null,"funder_award_id":"71531001","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":54,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1987431925","https://openalex.org/W2027731328","https://openalex.org/W2059745395","https://openalex.org/W2108920354","https://openalex.org/W2131494463","https://openalex.org/W2133266261","https://openalex.org/W2140310134","https://openalex.org/W2163922914","https://openalex.org/W2187089797","https://openalex.org/W2295739661","https://openalex.org/W2511264801","https://openalex.org/W2515144511","https://openalex.org/W2548570154","https://openalex.org/W2593507512","https://openalex.org/W2604433096","https://openalex.org/W2604662567","https://openalex.org/W2605350416","https://openalex.org/W2614794251","https://openalex.org/W2767669124","https://openalex.org/W2783565819","https://openalex.org/W2783944588","https://openalex.org/W2798972759","https://openalex.org/W2802187397","https://openalex.org/W2893359107","https://openalex.org/W2900229157","https://openalex.org/W2911778742","https://openalex.org/W2938315199","https://openalex.org/W2945623882","https://openalex.org/W2945827670","https://openalex.org/W2951008357","https://openalex.org/W2962992837","https://openalex.org/W2963085847","https://openalex.org/W2963367478","https://openalex.org/W2963448850","https://openalex.org/W2963668762","https://openalex.org/W2964052347","https://openalex.org/W2964068143","https://openalex.org/W2964182926","https://openalex.org/W2966349618","https://openalex.org/W2979450518","https://openalex.org/W2997261254","https://openalex.org/W2998431760","https://openalex.org/W3097991661","https://openalex.org/W3100278010","https://openalex.org/W3100591234","https://openalex.org/W3104439459","https://openalex.org/W4295312788","https://openalex.org/W6631190155","https://openalex.org/W6638318767","https://openalex.org/W6679844565","https://openalex.org/W6680830989","https://openalex.org/W6766978945","https://openalex.org/W6772360137"],"related_works":["https://openalex.org/W2348159088","https://openalex.org/W2893089803","https://openalex.org/W2950576907","https://openalex.org/W2248517341","https://openalex.org/W2074252522","https://openalex.org/W1997045192","https://openalex.org/W4223991077","https://openalex.org/W3004317398","https://openalex.org/W3196754007","https://openalex.org/W2081364100"],"abstract_inverted_index":{"Given":[0],"the":[1,31,151,164,185,193],"effectiveness":[2],"and":[3,18,112,163,182,192],"ease":[4],"of":[5,27,54,138],"use,":[6],"Item-based":[7],"Collaborative":[8,77],"Filtering":[9,78],"(ICF)":[10],"methods":[11],"have":[12],"been":[13],"broadly":[14],"used":[15],"in":[16,22,30,105],"industry":[17],"are":[19,157],"widely":[20],"investigated":[21],"recent":[23],"years.":[24],"The":[25],"key":[26],"ICF":[28],"lies":[29],"similarity":[32],"measurement":[33],"between":[34,134],"items,":[35],"which":[36,71,141],"however":[37],"is":[38,79,85,126,167],"a":[39,61,72,87,114,139],"coarse-grained":[40],"numerical":[41],"value":[42],"that":[43,92],"can":[44],"hardly":[45],"capture":[46],"users'":[47,145],"fine-grained":[48,146],"preferences":[49,147],"toward":[50],"different":[51],"attributed":[52],"aspects":[53],"items.":[55],"In":[56,174],"this":[57,67],"paper,":[58],"we":[59],"propose":[60],"model":[62,91],"called":[63,75],"REDA":[64,84,166,176],"to":[65,169,187],"address":[66],"challenge,":[68],"based":[69],"on":[70,159],"new":[73],"paradigm":[74],"Relation-based":[76],"designed":[80],"for":[81,99,119,195],"high-performance":[82],"recommendation.":[83,197],"essentially":[86],"deep":[88],"neural":[89],"network":[90],"employs":[93,113],"an":[94],"item":[95,107,131,190],"relation":[96,132,183],"embedding":[97,108,125],"scheme":[98,118],"inter-item":[100],"relations":[101],"representation.":[102],"It":[103],"features":[104],"multi-decomposed":[106],"with":[109],"dual-attention":[110],"refinement":[111],"novel":[115],"relation-wise":[116],"optimization":[117],"end-to-end":[120],"learning.":[121],"A":[122],"relational":[123],"user":[124],"then":[127],"proposed":[128,165],"by":[129],"aggregating":[130],"embeddings":[133],"all":[135],"purchased":[136],"items":[137],"user,":[140],"not":[142],"only":[143],"profiles":[144],"but":[148],"also":[149],"alleviates":[150],"data":[152,181],"sparsity":[153],"problem.":[154],"Extensive":[155],"experiments":[156],"conducted":[158],"five":[160],"real-world":[161],"datasets":[162],"shown":[168],"outperform":[170],"ten":[171],"state-of-the-art":[172],"methods.":[173],"particular,":[175],"shows":[177],"great":[178],"robustness":[179],"against":[180],"sparsity,":[184],"ability":[186],"learn":[188],"explainable":[189],"aspects,":[191],"potential":[194],"large-scale":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}