{"id":"https://openalex.org/W2966199682","doi":"https://doi.org/10.24963/ijcai.2019/619","title":"Collaborative Metric Learning with Memory Network for Multi-Relational Recommender Systems","display_name":"Collaborative Metric Learning with Memory Network for Multi-Relational Recommender Systems","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2966199682","doi":"https://doi.org/10.24963/ijcai.2019/619","mag":"2966199682"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/619","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/619","pdf_url":"https://www.ijcai.org/proceedings/2019/0619.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0619.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101977042","display_name":"Zhou Xiao","orcid":"https://orcid.org/0000-0002-0868-764X"},"institutions":[{"id":"https://openalex.org/I241749","display_name":"University of Cambridge","ror":"https://ror.org/013meh722","country_code":"GB","type":"education","lineage":["https://openalex.org/I241749"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Xiao Zhou","raw_affiliation_strings":["Department of Computer Science and Technology, University of Cambridge, UK"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, University of Cambridge, UK","institution_ids":["https://openalex.org/I241749"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114860516","display_name":"Danyang Liu","orcid":"https://orcid.org/0000-0002-5078-6908"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Danyang Liu","raw_affiliation_strings":["University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087106517","display_name":"Jianxun Lian","orcid":"https://orcid.org/0000-0003-3108-5601"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxun Lian","raw_affiliation_strings":["Microsoft Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044651577","display_name":"Xing Xie","orcid":"https://orcid.org/0000-0002-8608-8482"},"institutions":[{"id":"https://openalex.org/I4210113369","display_name":"Microsoft Research Asia (China)","ror":"https://ror.org/0300m5276","country_code":"CN","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210113369"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xing Xie","raw_affiliation_strings":["Microsoft Research, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Microsoft Research, Beijing, China","institution_ids":["https://openalex.org/I4210113369"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101977042"],"corresponding_institution_ids":["https://openalex.org/I241749"],"apc_list":null,"apc_paid":null,"fwci":7.1222,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.97085993,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4454","last_page":"4460"},"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":0.9860000014305115,"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/T10028","display_name":"Topic Modeling","score":0.9419999718666077,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.829160213470459},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.8275923728942871},{"id":"https://openalex.org/keywords/purchasing","display_name":"Purchasing","score":0.5457569360733032},{"id":"https://openalex.org/keywords/variety","display_name":"Variety (cybernetics)","score":0.5241665840148926},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5202347040176392},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.45947614312171936},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36361488699913025},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35726460814476013},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.32961905002593994}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.829160213470459},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.8275923728942871},{"id":"https://openalex.org/C2778813691","wikidata":"https://www.wikidata.org/wiki/Q1369832","display_name":"Purchasing","level":2,"score":0.5457569360733032},{"id":"https://openalex.org/C136197465","wikidata":"https://www.wikidata.org/wiki/Q1729295","display_name":"Variety (cybernetics)","level":2,"score":0.5241665840148926},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5202347040176392},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.45947614312171936},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36361488699913025},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35726460814476013},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32961905002593994},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/619","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/619","pdf_url":"https://www.ijcai.org/proceedings/2019/0619.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/619","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/619","pdf_url":"https://www.ijcai.org/proceedings/2019/0619.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.6899999976158142,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2966199682.pdf","grobid_xml":"https://content.openalex.org/works/W2966199682.grobid-xml"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1502375784","https://openalex.org/W1530276735","https://openalex.org/W2101409192","https://openalex.org/W2105953200","https://openalex.org/W2127795553","https://openalex.org/W2140310134","https://openalex.org/W2517217469","https://openalex.org/W2517388038","https://openalex.org/W2604433096","https://openalex.org/W2607068358","https://openalex.org/W2741859754","https://openalex.org/W2783944588","https://openalex.org/W2798881875","https://openalex.org/W2798972759","https://openalex.org/W2808446163","https://openalex.org/W3099237846","https://openalex.org/W3100591234","https://openalex.org/W3106062149","https://openalex.org/W3170187879","https://openalex.org/W4231990774"],"related_works":["https://openalex.org/W4390273403","https://openalex.org/W4386781444","https://openalex.org/W2150182025","https://openalex.org/W3092950680","https://openalex.org/W3197542405","https://openalex.org/W2056712470","https://openalex.org/W3125580266","https://openalex.org/W4288390103","https://openalex.org/W4317039510","https://openalex.org/W2351217280"],"abstract_inverted_index":{"The":[0],"success":[1],"of":[2,15,24,38,49,74,81,95,103,149,154,173],"recommender":[3,66],"systems":[4,67],"in":[5,35,100,115,147,169],"modern":[6],"online":[7,33],"platforms":[8],"is":[9,98],"inseparable":[10],"from":[11,63],"the":[12,89,92,150,161],"accurate":[13],"capture":[14],"users'":[16],"personal":[17],"tastes.":[18],"In":[19],"everyday":[20],"life,":[21],"large":[22],"amounts":[23],"user":[25,50,96,155],"feedback":[26,51,145],"data":[27],"are":[28],"created":[29],"along":[30],"with":[31,54,105],"user-item":[32,82,136],"interactions":[34,83,104],"a":[36,71,120,170],"variety":[37],"ways,":[39],"such":[40],"as":[41],"browsing,":[42],"purchasing,":[43],"and":[44,107,152,179],"sharing.":[45],"These":[46],"multiple":[47,79],"types":[48,80,102,146],"provide":[52],"us":[53,141],"tremendous":[55],"opportunities":[56],"to":[57,142],"detect":[58],"individuals'":[59],"fine-grained":[60,135],"preferences.":[61,156],"Different":[62],"most":[64],"existing":[65],"that":[68,91,160],"rely":[69],"on":[70,88],"single":[72],"type":[73],"feedback,":[75],"we":[76,118],"advocate":[77],"incorporating":[78],"for":[84],"better":[85],"recommendations.":[86,181],"Based":[87],"observation":[90],"underlying":[93],"spectrum":[94],"preferences":[97],"reflected":[99],"various":[101],"items":[106],"can":[108,131],"be":[109],"uncovered":[110],"by":[111],"latent":[112],"relational":[113],"learning":[114,123],"metric":[116],"space,":[117],"propose":[119],"unified":[121],"neural":[122],"framework,":[124],"named":[125],"Multi-Relational":[126],"Memory":[127],"Network":[128],"(MRMN).":[129],"It":[130],"not":[132],"only":[133],"model":[134,164],"relations":[137],"but":[138],"also":[139],"enable":[140],"discriminate":[143],"between":[144],"terms":[148],"strength":[151],"diversity":[153],"Extensive":[157],"experiments":[158],"show":[159],"proposed":[162],"MRMN":[163],"outperforms":[165],"competitive":[166],"state-of-the-art":[167],"algorithms":[168],"wide":[171],"range":[172],"scenarios,":[174],"including":[175],"e-commerce,":[176],"local":[177],"services,":[178],"job":[180]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
