{"id":"https://openalex.org/W3093922720","doi":"https://doi.org/10.1145/3340531.3411947","title":"Multi-modal Knowledge Graphs for Recommender Systems","display_name":"Multi-modal Knowledge Graphs for Recommender Systems","publication_year":2020,"publication_date":"2020-10-19","ids":{"openalex":"https://openalex.org/W3093922720","doi":"https://doi.org/10.1145/3340531.3411947","mag":"3093922720"},"language":"en","primary_location":{"id":"doi:10.1145/3340531.3411947","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3411947","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information &amp; Knowledge Management","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/A5027072710","display_name":"Rui Sun","orcid":"https://orcid.org/0000-0001-5429-978X"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Sun","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108060642","display_name":"Xuezhi Cao","orcid":"https://orcid.org/0000-0002-7044-1341"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xuezhi Cao","raw_affiliation_strings":["Meituan-Dianping Group, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan-Dianping Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060365518","display_name":"Yan Zhao","orcid":"https://orcid.org/0000-0002-0242-3707"},"institutions":[{"id":"https://openalex.org/I891191580","display_name":"Aalborg University","ror":"https://ror.org/04m5j1k67","country_code":"DK","type":"education","lineage":["https://openalex.org/I891191580"]}],"countries":["DK"],"is_corresponding":false,"raw_author_name":"Yan Zhao","raw_affiliation_strings":["Aalborg University, Aalborg, Denmark"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aalborg University, Aalborg, Denmark","institution_ids":["https://openalex.org/I891191580"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024464904","display_name":"Junchen Wan","orcid":"https://orcid.org/0000-0003-1831-2005"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Junchen Wan","raw_affiliation_strings":["Meituan-Dianping Group, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan-Dianping Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063459528","display_name":"Kun Zhou","orcid":"https://orcid.org/0000-0003-0650-9521"},"institutions":[{"id":"https://openalex.org/I78988378","display_name":"Renmin University of China","ror":"https://ror.org/041pakw92","country_code":"CN","type":"education","lineage":["https://openalex.org/I78988378"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Zhou","raw_affiliation_strings":["Renmin University of China, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Renmin University of China, Beijing, China","institution_ids":["https://openalex.org/I78988378"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101586840","display_name":"Fuzheng Zhang","orcid":"https://orcid.org/0000-0002-6079-6392"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fuzheng Zhang","raw_affiliation_strings":["Meituan-Dianping Group, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan-Dianping Group, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100741750","display_name":"Zhongyuan Wang","orcid":"https://orcid.org/0000-0002-9796-488X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhongyuan Wang","raw_affiliation_strings":["Meituan-Dianping Group, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Meituan-Dianping Group, Beijing, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100603979","display_name":"Kai Zheng","orcid":"https://orcid.org/0000-0002-0217-3998"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Zheng","raw_affiliation_strings":["University of Electronic Science and Technology of China, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Electronic Science and Technology of China, Chengdu, China","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5027072710"],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":17.0055,"has_fulltext":false,"cited_by_count":259,"citation_normalized_percentile":{"value":0.99360525,"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":"1405","last_page":"1414"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9995999932289124,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10203","display_name":"Recommender Systems and Techniques","score":0.9987999796867371,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.8676983714103699},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8418412208557129},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.7599927186965942},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6263889074325562},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.6251904964447021},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4893207252025604},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4681459069252014},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.46653181314468384},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.41785016655921936},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38676029443740845},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3179120421409607},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.31620246171951294}],"concepts":[{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8676983714103699},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8418412208557129},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.7599927186965942},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6263889074325562},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.6251904964447021},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4893207252025604},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4681459069252014},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.46653181314468384},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.41785016655921936},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38676029443740845},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3179120421409607},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.31620246171951294},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"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/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3340531.3411947","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3340531.3411947","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 29th ACM International Conference on Information &amp; Knowledge Management","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/e4faa720-8c75-4c51-ae4f-4042af2fc6a3","is_oa":false,"landing_page_url":"https://vbn.aau.dk/da/publications/e4faa720-8c75-4c51-ae4f-4042af2fc6a3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401731","display_name":"VBN Forskningsportal (Aalborg Universitet)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I891191580","host_organization_name":"Aalborg University","host_organization_lineage":["https://openalex.org/I891191580"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sun , R , Cao , X , Zhao , Y , Wan , J , Zhou , K , Zhang , F , Wang , Z &amp; Zheng , K 2020 , Multi-modal Knowledge Graphs for Recommender Systems . in CIKM 2020 - Proceedings of the 29th ACM International Conference on Information and Knowledge Management . Association for Computing Machinery , pp. 1405-1414 , 29th ACM International Conference on Information and Knowledge Management, CIKM 2020 , Virtual, Online , Ireland , 19/10/2020 . https://doi.org/10.1145/3340531.3411947","raw_type":"contributionToPeriodical"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1905882502","https://openalex.org/W2010187764","https://openalex.org/W2054141820","https://openalex.org/W2108598243","https://openalex.org/W2127795553","https://openalex.org/W2153579005","https://openalex.org/W2194775991","https://openalex.org/W2743159750","https://openalex.org/W2752172973","https://openalex.org/W2759136286","https://openalex.org/W2772021946","https://openalex.org/W2774837955","https://openalex.org/W2792839191","https://openalex.org/W2807480793","https://openalex.org/W2895837054","https://openalex.org/W2914874661","https://openalex.org/W2945623882","https://openalex.org/W2950292336","https://openalex.org/W2963323306","https://openalex.org/W2963403868","https://openalex.org/W2963606508","https://openalex.org/W2963869731","https://openalex.org/W2963911286","https://openalex.org/W2963954913","https://openalex.org/W2964010806","https://openalex.org/W2964737815","https://openalex.org/W2982108874","https://openalex.org/W3098087397","https://openalex.org/W3098923689","https://openalex.org/W3099387504"],"related_works":["https://openalex.org/W2604454537","https://openalex.org/W2883748392","https://openalex.org/W2897702399","https://openalex.org/W4206028705","https://openalex.org/W2757431232","https://openalex.org/W2808284704","https://openalex.org/W2954554213","https://openalex.org/W2251363251","https://openalex.org/W4206547516","https://openalex.org/W4293236197"],"abstract_inverted_index":{"Recommender":[0],"systems":[1,81],"have":[2],"shown":[3],"great":[4],"potential":[5],"to":[6,77,94,152],"solve":[7],"the":[8,52,103,111,118,154],"information":[9,96],"explosion":[10],"problem":[11],"and":[12,24,59,100],"enhance":[13,79],"user":[14],"experience":[15],"in":[16,28,61],"various":[17],"online":[18],"applications.":[19],"To":[20,110],"tackle":[21],"data":[22,55],"sparsity":[23],"cold":[25],"start":[26],"problems":[27],"recommender":[29,80,127],"systems,":[30],"researchers":[31],"propose":[32,70,88],"knowledge":[33,42,63,124],"graphs":[34,64],"(KGs)":[35],"based":[36],"recommendations":[37],"by":[38,82],"leveraging":[39,83],"valuable":[40],"external":[41],"as":[43],"auxiliary":[44],"information.":[45],"However,":[46],"most":[47],"of":[48,54,113,141,156],"these":[49],"works":[50],"ignore":[51],"variety":[53],"types":[56],"(e.g.,":[57],"texts":[58],"images)":[60],"multi-modal":[62,84,90,123],"(MMKGs).":[65],"In":[66],"this":[67,116],"paper,":[68],"we":[69,87],"Multi-modal":[71],"Knowledge":[72],"Graph":[73],"Attention":[74],"Network":[75],"(MKGAT)":[76],"better":[78],"knowledge.":[85],"Specifically,":[86],"a":[89],"graph":[91,125],"attention":[92],"technique":[93],"conduct":[95,130],"propagation":[97],"over":[98],"MMKGs,":[99],"then":[101],"use":[102],"resulting":[104],"aggregated":[105],"embedding":[106],"representation":[107],"for":[108],"recommendation.":[109],"best":[112],"our":[114,145],"knowledge,":[115],"is":[117],"first":[119],"work":[120],"that":[121,144],"incorporates":[122],"into":[126],"systems.":[128],"We":[129],"extensive":[131],"experiments":[132],"on":[133],"two":[134],"real":[135],"datasets":[136],"from":[137],"different":[138],"domains,":[139],"results":[140],"which":[142],"demonstrate":[143],"model":[146],"MKGAT":[147],"can":[148],"successfully":[149],"employ":[150],"MMKGs":[151],"improve":[153],"quality":[155],"recommendation":[157],"system.":[158]},"counts_by_year":[{"year":2026,"cited_by_count":15},{"year":2025,"cited_by_count":50},{"year":2024,"cited_by_count":69},{"year":2023,"cited_by_count":62},{"year":2022,"cited_by_count":50},{"year":2021,"cited_by_count":13}],"updated_date":"2026-05-31T08:46:17.908082","created_date":"2025-10-10T00:00:00"}
