{"id":"https://openalex.org/W4290875571","doi":"https://doi.org/10.1145/3534678.3539458","title":"User-Event Graph Embedding Learning for Context-Aware Recommendation","display_name":"User-Event Graph Embedding Learning for Context-Aware Recommendation","publication_year":2022,"publication_date":"2022-08-12","ids":{"openalex":"https://openalex.org/W4290875571","doi":"https://doi.org/10.1145/3534678.3539458"},"language":"en","primary_location":{"id":"doi:10.1145/3534678.3539458","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539458","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery 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 28th ACM SIGKDD Conference on Knowledge Discovery 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/A5003106644","display_name":"Dugang Liu","orcid":"https://orcid.org/0000-0003-3612-709X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dugang Liu","raw_affiliation_strings":["Shenzhen University & Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University & Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027493008","display_name":"Mingkai He","orcid":"https://orcid.org/0000-0002-3017-9596"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingkai He","raw_affiliation_strings":["Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019495818","display_name":"Jinwei Luo","orcid":"https://orcid.org/0000-0002-1415-5826"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinwei Luo","raw_affiliation_strings":["Shenzhen University, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University, Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087353852","display_name":"Jiangxu Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiangxu Lin","raw_affiliation_strings":["Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100377147","display_name":"Meng Wang","orcid":"https://orcid.org/0000-0002-3094-7735"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Wang","raw_affiliation_strings":["Southeast University, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Southeast University, Nanjing, China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103197292","display_name":"Xiaolian Zhang","orcid":"https://orcid.org/0000-0002-9641-2848"},"institutions":[{"id":"https://openalex.org/I2250955327","display_name":"Huawei Technologies (China)","ror":"https://ror.org/00cmhce21","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250955327"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaolian Zhang","raw_affiliation_strings":["Huawei Technologies Co Ltd, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co Ltd, Shenzhen, China","institution_ids":["https://openalex.org/I2250955327"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073490832","display_name":"Weike Pan","orcid":"https://orcid.org/0000-0001-6326-9531"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weike Pan","raw_affiliation_strings":["Shenzhen University & Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University & Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5033128202","display_name":"Ming Zhong","orcid":"https://orcid.org/0000-0001-9376-818X"},"institutions":[{"id":"https://openalex.org/I180726961","display_name":"Shenzhen University","ror":"https://ror.org/01vy4gh70","country_code":"CN","type":"education","lineage":["https://openalex.org/I180726961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhong Ming","raw_affiliation_strings":["Shenzhen University & Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Shenzhen University & Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, China","institution_ids":["https://openalex.org/I180726961"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5003106644"],"corresponding_institution_ids":["https://openalex.org/I180726961"],"apc_list":null,"apc_paid":null,"fwci":1.8935,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.88355568,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1051","last_page":"1059"},"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9958999752998352,"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":0.9316999912261963,"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":0.8009031414985657},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.6087964177131653},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.546403706073761},{"id":"https://openalex.org/keywords/call-graph","display_name":"Call graph","score":0.5305823683738708},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.5148584246635437},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4740055501461029},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4698903560638428},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.4631580412387848},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.41205736994743347},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4100058674812317},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3164922297000885},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3017694056034088}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8009031414985657},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.6087964177131653},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.546403706073761},{"id":"https://openalex.org/C102379954","wikidata":"https://www.wikidata.org/wiki/Q2589940","display_name":"Call graph","level":2,"score":0.5305823683738708},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.5148584246635437},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4740055501461029},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4698903560638428},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.4631580412387848},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.41205736994743347},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4100058674812317},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3164922297000885},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3017694056034088},{"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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3534678.3539458","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3534678.3539458","pdf_url":null,"source":{"id":"https://openalex.org/S4363608767","display_name":"Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery 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 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2330719858","display_name":null,"funder_award_id":"61836005,62172283","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1998889130","https://openalex.org/W2002834872","https://openalex.org/W2009385725","https://openalex.org/W2030385985","https://openalex.org/W2054141820","https://openalex.org/W2102937240","https://openalex.org/W2547424360","https://openalex.org/W2567289326","https://openalex.org/W2624431344","https://openalex.org/W2793768763","https://openalex.org/W2809418595","https://openalex.org/W2896691185","https://openalex.org/W2911286998","https://openalex.org/W2945827670","https://openalex.org/W2951661358","https://openalex.org/W2955380732","https://openalex.org/W2963146368","https://openalex.org/W2963323306","https://openalex.org/W2979450518","https://openalex.org/W3003875435","https://openalex.org/W3012780388","https://openalex.org/W3021904157","https://openalex.org/W3034329572","https://openalex.org/W3045200674","https://openalex.org/W3083824577","https://openalex.org/W3088364587","https://openalex.org/W3094605801","https://openalex.org/W3100278010","https://openalex.org/W3104030692","https://openalex.org/W3104439459","https://openalex.org/W3104763847","https://openalex.org/W3153325943","https://openalex.org/W3154246858","https://openalex.org/W3167730891","https://openalex.org/W3201053014","https://openalex.org/W3204808432","https://openalex.org/W3211143493","https://openalex.org/W4226380897","https://openalex.org/W4231054948","https://openalex.org/W4247692230","https://openalex.org/W4284675146","https://openalex.org/W4294558607"],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W3176564347","https://openalex.org/W2355833770","https://openalex.org/W1985458517","https://openalex.org/W3031039437","https://openalex.org/W183202219","https://openalex.org/W3095877357","https://openalex.org/W2072565696","https://openalex.org/W2050451745","https://openalex.org/W2378903222"],"abstract_inverted_index":{"Most":[0],"methods":[1],"for":[2,86],"context-aware":[3,162],"recommendation":[4,154,163],"focus":[5],"on":[6,103,132,232],"improving":[7],"the":[8,14,29,32,38,41,92,106,120,133,147,166,173,184,189,203,220,224,238],"feature":[9,167],"interaction":[10],"layer,":[11],"but":[12,211],"overlook":[13],"embedding":[15,19,56],"layer.":[16],"However,":[17],"an":[18],"layer":[20],"with":[21,172,193],"random":[22],"initialization":[23],"often":[24],"suffers":[25],"in":[26,216],"practice":[27],"from":[28,199],"sparsity":[30,64],"of":[31,105,123,183,223,242],"contextual":[33,107,190,225],"features,":[34],"as":[35,37,141],"well":[36],"interactions":[39],"between":[40],"users":[42],"(or":[43],"items)":[44],"and":[45,89,240,245],"context.":[46],"In":[47],"this":[48],"paper,":[49],"we":[50,178,228],"propose":[51,208],"a":[52,73,81,110,128,142,153,180,209],"novel":[53],"user-event":[54,82,111,134],"graph":[55,74,83,113],"learning":[57],"(UEG-EL)":[58],"framework":[59],"to":[60,79,118,144,158,218,236],"address":[61],"these":[62],"two":[63],"challenges.":[65],"Specifically,":[66],"our":[67,243],"UEG-EL":[68,244],"contains":[69],"three":[70,233],"modules:":[71],"1)":[72],"construction":[75],"module":[76,115,155],"is":[77,116,156],"used":[78],"obtain":[80,119],"containing":[84],"nodes":[85,94,104],"users,":[87],"intents":[88],"items,":[90],"where":[91,136,165],"intent":[93,99,138],"are":[95,169],"generated":[96],"by":[97,126],"applying":[98],"node":[100,139],"attention":[101],"(INA)":[102],"features;":[108,151],"2)":[109],"collaborative":[112],"convolution":[114,130],"designed":[117],"refined":[121,175],"embeddings":[122,168],"all":[124],"features":[125,191],"executing":[127],"new":[129],"strategy":[131],"graph,":[135],"each":[137],"acts":[140],"hub":[143],"efficiently":[145],"propagate":[146],"information":[148,221],"among":[149],"different":[150],"3)":[152],"equipped":[157],"integrate":[159],"some":[160],"existing":[161],"model,":[164],"directly":[170],"initialized":[171],"obtained":[174],"embeddings.":[176],"Moreover,":[177],"identify":[179],"unique":[181],"challenge":[182],"basic":[185],"framework,":[186],"that":[187],"is,":[188],"associated":[192],"too":[194],"many":[195],"instances":[196],"may":[197],"suffer":[198],"noise":[200],"when":[201],"aggregating":[202],"information.":[204],"We":[205],"thus":[206],"further":[207],"simple":[210],"effective":[212],"variant,":[213],"i.e.,":[214],"UEG-EL-V,":[215],"order":[217],"prune":[219],"propagation":[222],"features.":[226],"Finally,":[227],"conduct":[229],"extensive":[230],"experiments":[231],"public":[234],"datasets":[235],"verify":[237],"effectiveness":[239],"compatibility":[241],"its":[246],"variant.":[247]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}