{"id":"https://openalex.org/W3199744737","doi":"https://doi.org/10.1145/3460231.3474239","title":"Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems","display_name":"Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems","publication_year":2021,"publication_date":"2021-09-13","ids":{"openalex":"https://openalex.org/W3199744737","doi":"https://doi.org/10.1145/3460231.3474239","mag":"3199744737"},"language":"en","primary_location":{"id":"doi:10.1145/3460231.3474239","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460231.3474239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2111.04282","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089832695","display_name":"Danni Peng","orcid":"https://orcid.org/0000-0003-0884-9597"},"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":"Danni Peng","raw_affiliation_strings":["Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082984558","display_name":"Sinno Jialin Pan","orcid":"https://orcid.org/0000-0001-6565-3836"},"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":"Sinno Jialin Pan","raw_affiliation_strings":["School of Computer Science and Engineering Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100436659","display_name":"Jie Zhang","orcid":"https://orcid.org/0000-0001-8996-7581"},"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":"Jie Zhang","raw_affiliation_strings":["School of Computer Science and Engineering Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076875538","display_name":"Anxiang Zeng","orcid":"https://orcid.org/0000-0003-3869-5357"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anxiang Zeng","raw_affiliation_strings":["NTU SCSE, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"NTU SCSE, Singapore","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.1145,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.96538751,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"411","last_page":"421"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9997000098228455,"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":0.9997000098228455,"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/T10028","display_name":"Topic Modeling","score":0.996399998664856,"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/T12535","display_name":"Machine Learning and Data Classification","score":0.9926000237464905,"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":0.8609887361526489},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.7525365352630615},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7433584928512573},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.7089307308197021},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5976870059967041},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5732447504997253},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5391350984573364},{"id":"https://openalex.org/keywords/forgetting","display_name":"Forgetting","score":0.46103620529174805},{"id":"https://openalex.org/keywords/rss","display_name":"RSS","score":0.4253199100494385},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4209684729576111},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3832656741142273},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.13807660341262817},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.11677801609039307}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8609887361526489},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.7525365352630615},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7433584928512573},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.7089307308197021},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5976870059967041},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5732447504997253},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5391350984573364},{"id":"https://openalex.org/C7149132","wikidata":"https://www.wikidata.org/wiki/Q1377840","display_name":"Forgetting","level":2,"score":0.46103620529174805},{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.4253199100494385},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4209684729576111},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3832656741142273},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.13807660341262817},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.11677801609039307},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3460231.3474239","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3460231.3474239","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Fifteenth ACM Conference on Recommender Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2111.04282","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.04282","pdf_url":"https://arxiv.org/pdf/2111.04282","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2111.04282","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2111.04282","pdf_url":"https://arxiv.org/pdf/2111.04282","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.47999998927116394,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W30495595","https://openalex.org/W1509627219","https://openalex.org/W1924770834","https://openalex.org/W1990846291","https://openalex.org/W2001575213","https://openalex.org/W2061737399","https://openalex.org/W2077927809","https://openalex.org/W2116522068","https://openalex.org/W2475334473","https://openalex.org/W2517540742","https://openalex.org/W2519084221","https://openalex.org/W2560647685","https://openalex.org/W2604662567","https://openalex.org/W2723293840","https://openalex.org/W2760377357","https://openalex.org/W2799117791","https://openalex.org/W2893044927","https://openalex.org/W2903183390","https://openalex.org/W2951001079","https://openalex.org/W2951431594","https://openalex.org/W2963072899","https://openalex.org/W2963559848","https://openalex.org/W2964189064","https://openalex.org/W3035086011","https://openalex.org/W3038719422","https://openalex.org/W3045108742","https://openalex.org/W3082291914","https://openalex.org/W3083058384","https://openalex.org/W3088966581","https://openalex.org/W3104003068","https://openalex.org/W3105297929","https://openalex.org/W3106035229","https://openalex.org/W3201053014","https://openalex.org/W4301163820","https://openalex.org/W4319988532"],"related_works":["https://openalex.org/W4362597605","https://openalex.org/W1574414179","https://openalex.org/W3009056573","https://openalex.org/W4297676672","https://openalex.org/W2922073769","https://openalex.org/W4281702477","https://openalex.org/W2490526372","https://openalex.org/W4376166922","https://openalex.org/W4378510483","https://openalex.org/W3177075132"],"abstract_inverted_index":{"Recommender":[0],"Systems":[1],"(RSs)":[2],"in":[3],"real-world":[4],"applications":[5],"often":[6],"deal":[7],"with":[8,117],"billions":[9],"of":[10,77,87],"user":[11],"interactions":[12],"daily.":[13],"To":[14,54],"capture":[15,104],"the":[16,26,31,39,48,85,88,105,118,138],"most":[17],"recent":[18],"trends":[19],"effectively,":[20],"it":[21],"is":[22],"common":[23],"to":[24,42,47,93,99,103,114],"update":[25],"model":[27,73],"incrementally":[28],"using":[29],"only":[30,124],"newly":[32],"arrived":[33],"data.":[34],"However,":[35],"this":[36,56],"may":[37],"impede":[38],"model\u2019s":[40],"ability":[41,102],"retain":[43],"long-term":[44,106],"information":[45],"due":[46],"potential":[49],"overfitting":[50],"and":[51,160],"forgetting":[52],"issues.":[53],"address":[55],"problem,":[57],"we":[58,91,148],"propose":[59,92],"a":[60,70,75,81,142],"novel":[61,112],"Adaptive":[62],"Sequential":[63],"Model":[64],"Generation":[65],"(ASMG)":[66],"framework,":[67],"which":[68,122],"generates":[69],"better":[71],"serving":[72],"from":[74],"sequence":[76],"historical":[78],"models":[79],"via":[80],"meta":[82,89,120],"generator.":[83],"For":[84],"design":[86],"generator,":[90,121],"employ":[94],"Gated":[95],"Recurrent":[96],"Units":[97],"(GRUs)":[98],"leverage":[100],"its":[101,126],"dependencies.":[107],"We":[108],"further":[109],"introduce":[110],"some":[111],"strategies":[113],"apply":[115],"together":[116],"GRU":[119],"not":[123],"improve":[125],"computational":[127],"efficiency":[128],"but":[129],"also":[130],"enable":[131],"more":[132],"accurate":[133],"sequential":[134],"modeling.":[135],"By":[136],"instantiating":[137],"model-agnostic":[139],"framework":[140],"on":[141,156],"general":[143],"deep":[144],"learning-based":[145],"RS":[146],"model,":[147],"demonstrate":[149],"that":[150],"our":[151],"method":[152],"achieves":[153],"state-of-the-art":[154],"performance":[155],"three":[157],"public":[158],"datasets":[159],"one":[161],"industrial":[162],"dataset.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":5}],"updated_date":"2026-08-05T07:39:15.569665","created_date":"2025-10-10T00:00:00"}