{"id":"https://openalex.org/W3160913626","doi":"https://doi.org/10.1145/3488560.3498371","title":"Long Short-Term Temporal Meta-learning in Online Recommendation","display_name":"Long Short-Term Temporal Meta-learning in Online Recommendation","publication_year":2022,"publication_date":"2022-02-11","ids":{"openalex":"https://openalex.org/W3160913626","doi":"https://doi.org/10.1145/3488560.3498371","mag":"3160913626"},"language":"en","primary_location":{"id":"doi:10.1145/3488560.3498371","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498371","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","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/A5101577090","display_name":"Ruobing Xie","orcid":"https://orcid.org/0000-0003-3170-5647"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ruobing Xie","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100744972","display_name":"Yalong Wang","orcid":"https://orcid.org/0000-0002-5477-4488"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yalong Wang","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100431163","display_name":"Rui Wang","orcid":"https://orcid.org/0000-0001-9048-2979"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Wang","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068483851","display_name":"Yuanfu Lu","orcid":"https://orcid.org/0000-0002-5743-3216"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanfu Lu","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037796706","display_name":"Yuanhang Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanhang Zou","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102973664","display_name":"Feng Xia","orcid":"https://orcid.org/0000-0001-5279-9908"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Xia","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023086553","display_name":"Leyu Lin","orcid":"https://orcid.org/0000-0001-5471-500X"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Leyu Lin","raw_affiliation_strings":["WeChat, Tencent, Beijing, China"],"affiliations":[{"raw_affiliation_string":"WeChat, Tencent, Beijing, China","institution_ids":["https://openalex.org/I2250653659"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5101577090"],"corresponding_institution_ids":["https://openalex.org/I2250653659"],"apc_list":null,"apc_paid":null,"fwci":4.1032,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.95066495,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1168","last_page":"1176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9871000051498413,"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":0.8880734443664551},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.7026276588439941},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.6849488615989685},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.6773860454559326},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.5830442905426025},{"id":"https://openalex.org/keywords/online-learning","display_name":"Online learning","score":0.5339556932449341},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5006420612335205},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.41736817359924316},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4084005057811737},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.37110525369644165},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.28772208094596863}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8880734443664551},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.7026276588439941},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.6849488615989685},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.6773860454559326},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.5830442905426025},{"id":"https://openalex.org/C2986087404","wikidata":"https://www.wikidata.org/wiki/Q15946010","display_name":"Online learning","level":2,"score":0.5339556932449341},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5006420612335205},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.41736817359924316},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4084005057811737},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37110525369644165},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.28772208094596863},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3488560.3498371","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3488560.3498371","pdf_url":null,"source":{"id":"https://openalex.org/S4363608885","display_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W2145680191","https://openalex.org/W2146456494","https://openalex.org/W2146502635","https://openalex.org/W2154851992","https://openalex.org/W2295739661","https://openalex.org/W2604662567","https://openalex.org/W2723293840","https://openalex.org/W2753433947","https://openalex.org/W2809307135","https://openalex.org/W2898085636","https://openalex.org/W2899457523","https://openalex.org/W2905432015","https://openalex.org/W2914953695","https://openalex.org/W2950421571","https://openalex.org/W2951775809","https://openalex.org/W2955624969","https://openalex.org/W2962745591","https://openalex.org/W2963323306","https://openalex.org/W2963522561","https://openalex.org/W2964983698","https://openalex.org/W2965898633","https://openalex.org/W2978745145","https://openalex.org/W2984100107","https://openalex.org/W2988777870","https://openalex.org/W2997130580","https://openalex.org/W2998528009","https://openalex.org/W3012847895","https://openalex.org/W3034329572","https://openalex.org/W3034345128","https://openalex.org/W3034418242","https://openalex.org/W3035313290","https://openalex.org/W3043239945","https://openalex.org/W3045108742","https://openalex.org/W3081320135","https://openalex.org/W3094390815","https://openalex.org/W3101704389","https://openalex.org/W3101707147","https://openalex.org/W3104097132","https://openalex.org/W3132008141","https://openalex.org/W3136606064","https://openalex.org/W3153108722","https://openalex.org/W3155450594","https://openalex.org/W3160558455","https://openalex.org/W3166827814","https://openalex.org/W3173331009","https://openalex.org/W3194486110","https://openalex.org/W4288080156","https://openalex.org/W6600371763"],"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/W4238861846"],"abstract_inverted_index":{"An":[0],"effective":[1],"online":[2,82,158,167],"recommendation":[3,21,168],"system":[4,169],"should":[5],"jointly":[6],"capture":[7,117],"users'":[8,15,118],"long-term":[9,92,112],"and":[10,23,62,94,99,104,111,157],"short-term":[11,97,110],"preferences":[12,113],"in":[13,50,58,89],"both":[14,155],"internal":[16,96],"behaviors":[17,25,49,88],"(from":[18,26],"the":[19,55],"target":[20],"task)":[22],"external":[24,63],"other":[27],"tasks).":[28],"However,":[29],"it":[30],"is":[31],"extremely":[32],"challenging":[33],"to":[34,38,54,107],"conduct":[35],"fast":[36,136],"adaptations":[37],"real-time":[39,59,119],"new":[40],"trends":[41],"while":[42],"making":[43],"full":[44],"use":[45],"of":[46,176],"all":[47],"historical":[48],"large-scale":[51],"systems,":[52],"due":[53],"real-world":[56],"limitations":[57],"training":[60,105],"efficiency":[61],"behavior":[64],"acquisition.":[65],"To":[66,115],"address":[67],"these":[68],"practical":[69],"challenges,":[70],"we":[71,121],"propose":[72,122],"a":[73,90,123,165],"novel":[74],"Long":[75],"Short-Term":[76],"Temporal":[77],"Meta-learning":[78],"framework":[79],"(LSTTM)":[80],"for":[81,135],"recommendation.":[83],"It":[84,160],"arranges":[85],"user":[86,109],"multi-source":[87],"global":[91],"graph":[93],"an":[95,131],"graph,":[98],"conducts":[100],"different":[101,142,146],"GAT-based":[102],"aggregators":[103],"strategies":[106],"learn":[108],"separately.":[114],"timely":[116],"interests,":[120],"temporal":[124],"meta-learning":[125],"method":[126],"based":[127],"on":[128,154,164],"MAML":[129],"under":[130],"asynchronous":[132],"optimization":[133],"strategy":[134],"adaptation,":[137],"which":[138],"regards":[139],"recommendations":[140],"at":[141],"time":[143],"periods":[144],"as":[145],"tasks.":[147],"In":[148],"experiments,":[149],"LSTTM":[150],"achieves":[151],"significant":[152],"improvements":[153],"offline":[156],"evaluations.":[159],"has":[161],"been":[162],"deployed":[163],"widely-used":[166],"named":[170],"WeChat":[171],"Top":[172],"Stories,":[173],"affecting":[174],"millions":[175],"users.":[177]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":3}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}