{"id":"https://openalex.org/W3081268349","doi":"https://doi.org/10.1145/3404555.3404641","title":"Attention-Based Graph Convolution Collaborative Filtering","display_name":"Attention-Based Graph Convolution Collaborative Filtering","publication_year":2020,"publication_date":"2020-04-23","ids":{"openalex":"https://openalex.org/W3081268349","doi":"https://doi.org/10.1145/3404555.3404641","mag":"3081268349"},"language":"en","primary_location":{"id":"doi:10.1145/3404555.3404641","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3404555.3404641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence","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/A5101631159","display_name":"Han Xiao","orcid":"https://orcid.org/0000-0002-3537-6812"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiao Han","raw_affiliation_strings":["Beijing University of Technology"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology","institution_ids":["https://openalex.org/I37796252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101905673","display_name":"Xiaobin Xu","orcid":"https://orcid.org/0000-0003-4279-1907"},"institutions":[{"id":"https://openalex.org/I37796252","display_name":"Beijing University of Technology","ror":"https://ror.org/037b1pp87","country_code":"CN","type":"education","lineage":["https://openalex.org/I37796252"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaobin Xu","raw_affiliation_strings":["Beijing University of Technology"],"affiliations":[{"raw_affiliation_string":"Beijing University of Technology","institution_ids":["https://openalex.org/I37796252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101631159"],"corresponding_institution_ids":["https://openalex.org/I37796252"],"apc_list":null,"apc_paid":null,"fwci":0.2669,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.64605435,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"58","last_page":"62"},"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":0.9815000295639038,"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":0.9623000025749207,"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":0.8227413892745972},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"Collaborative filtering","score":0.8027684688568115},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5540810227394104},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5244441628456116},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5210710763931274},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5175406336784363},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5149279832839966},{"id":"https://openalex.org/keywords/information-overload","display_name":"Information overload","score":0.49530187249183655},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4716933071613312},{"id":"https://openalex.org/keywords/learning-to-rank","display_name":"Learning to rank","score":0.4498157799243927},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.41355323791503906},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3838846683502197},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.38322713971138},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.38107675313949585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3651873469352722},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3189699351787567},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.124793142080307}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8227413892745972},{"id":"https://openalex.org/C21569690","wikidata":"https://www.wikidata.org/wiki/Q94702","display_name":"Collaborative filtering","level":3,"score":0.8027684688568115},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5540810227394104},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5244441628456116},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5210710763931274},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5175406336784363},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5149279832839966},{"id":"https://openalex.org/C186625053","wikidata":"https://www.wikidata.org/wiki/Q1130191","display_name":"Information overload","level":2,"score":0.49530187249183655},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4716933071613312},{"id":"https://openalex.org/C86037889","wikidata":"https://www.wikidata.org/wiki/Q4330127","display_name":"Learning to rank","level":3,"score":0.4498157799243927},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.41355323791503906},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3838846683502197},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.38322713971138},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.38107675313949585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3651873469352722},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3189699351787567},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.124793142080307},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3404555.3404641","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3404555.3404641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 6th International Conference on Computing and Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1662382123","https://openalex.org/W1966553486","https://openalex.org/W2054141820","https://openalex.org/W2082123959","https://openalex.org/W2468907370","https://openalex.org/W2519887557","https://openalex.org/W2525579820","https://openalex.org/W2624407581","https://openalex.org/W2783565819","https://openalex.org/W2788893025","https://openalex.org/W2801236524","https://openalex.org/W2802422126","https://openalex.org/W2894039884","https://openalex.org/W2963403868","https://openalex.org/W3100591234","https://openalex.org/W3106302634","https://openalex.org/W4301312111"],"related_works":["https://openalex.org/W2205442635","https://openalex.org/W3431530","https://openalex.org/W3173572738","https://openalex.org/W2167225238","https://openalex.org/W76049015","https://openalex.org/W2983582411","https://openalex.org/W4285502420","https://openalex.org/W2944402528","https://openalex.org/W2217104375","https://openalex.org/W3128140723"],"abstract_inverted_index":{"The":[0,144],"development":[1],"of":[2,26,61],"big":[3],"data":[4,21],"has":[5,22,37,47,151],"brought":[6,11],"changes":[7],"to":[8,15,83,112,127,138],"society":[9],"and":[10,43,75,87,115,122,163],"us":[12],"challenges.":[13],"How":[14],"extract":[16],"useful":[17],"information":[18,71,118,133],"from":[19],"complex":[20],"become":[23],"the":[24,59,65,69,73,76,89,103,108,124,129,149,156],"focus":[25],"research":[27],"in":[28,41],"recent":[29],"years.":[30],"Personalized":[31],"recommendation":[32],"as":[33,58,137],"an":[34],"effective":[35],"solution":[36],"received":[38],"widespread":[39],"attention":[40,104,125],"academia":[42],"industry.":[44],"Collaborative":[45],"filtering":[46,99],"been":[48],"widely":[49],"used":[50,159],"by":[51],"finding":[52],"users":[53],"with":[54],"similar":[55,62],"user":[56,74,114],"behaviors":[57],"preferences":[60],"users.":[63],"However,":[64],"existing":[66],"methods":[67],"ignore":[68],"interaction":[70,117,132],"between":[72],"item":[77,116],"during":[78],"feature":[79,85,120,142],"extraction,":[80],"which":[81,106],"leads":[82],"imperfect":[84],"extraction":[86],"affects":[88],"algorithm":[90],"effect.":[91],"This":[92],"paper":[93],"proposes":[94],"a":[95,152],"graph":[96,109],"convolution":[97,110],"collaborative":[98],"model":[100,126,150],"based":[101],"on":[102,155],"model,":[105],"uses":[107,123],"network":[111],"embed":[113],"into":[119],"vectors,":[121],"highlight":[128],"relatively":[130],"important":[131],"among":[134],"them,":[135],"so":[136],"obtain":[139],"more":[140],"excellent":[141],"vector.":[143],"experimental":[145],"results":[146],"show":[147],"that":[148],"good":[153],"effect":[154],"two":[157],"commonly":[158],"evaluation":[160],"metrics:":[161],"recall":[162],"normalized":[164],"discounted":[165],"cumulative":[166],"gain(NDCG).":[167]},"counts_by_year":[{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}