{"id":"https://openalex.org/W4323797284","doi":"https://doi.org/10.1109/access.2023.3254897","title":"Attention-Enhanced Graph Neural Networks With Global Context for Session-Based Recommendation","display_name":"Attention-Enhanced Graph Neural Networks With Global Context for Session-Based Recommendation","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4323797284","doi":"https://doi.org/10.1109/access.2023.3254897"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3254897","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3254897","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10064299.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10064299.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5071689964","display_name":"Yingpei Chen","orcid":"https://orcid.org/0000-0003-2605-6056"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingpei Chen","raw_affiliation_strings":["School of Computer and Information Science, Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-2605-6056","affiliations":[{"raw_affiliation_string":"School of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101579518","display_name":"Yan Tang","orcid":"https://orcid.org/0000-0003-2950-7967"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yan Tang","raw_affiliation_strings":["School of Computer and Information Science, Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0003-2950-7967","affiliations":[{"raw_affiliation_string":"School of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5055825962","display_name":"Yuan Yuan","orcid":"https://orcid.org/0000-0001-9678-3369"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Yuan","raw_affiliation_strings":["School of Computer and Information Science, Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0001-9678-3369","affiliations":[{"raw_affiliation_string":"School of Computer and Information Science, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5071689964"],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":5.6981,"has_fulltext":true,"cited_by_count":13,"citation_normalized_percentile":{"value":0.96031453,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"11","issue":null,"first_page":"26237","last_page":"26246"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9948999881744385,"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":0.9793000221252441,"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":0.8362222909927368},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.710110068321228},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5939269661903381},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.5861386656761169},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5753536224365234},{"id":"https://openalex.org/keywords/merge","display_name":"Merge (version control)","score":0.5709946751594543},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4791138172149658},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4663488268852234},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4437797963619232},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.4309280812740326},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4152677059173584},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.27598243951797485},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.262184739112854},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.14772933721542358}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8362222909927368},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.710110068321228},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5939269661903381},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.5861386656761169},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5753536224365234},{"id":"https://openalex.org/C197129107","wikidata":"https://www.wikidata.org/wiki/Q1921621","display_name":"Merge (version control)","level":2,"score":0.5709946751594543},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4791138172149658},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4663488268852234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4437797963619232},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.4309280812740326},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4152677059173584},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27598243951797485},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.262184739112854},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.14772933721542358}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2023.3254897","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3254897","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10064299.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:9ea327aaf21e4de2b15fc41c560f68c3","is_oa":true,"landing_page_url":"https://doaj.org/article/9ea327aaf21e4de2b15fc41c560f68c3","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 26237-26246 (2023)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3254897","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3254897","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10064299.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1997136459","https://openalex.org/W2042281163","https://openalex.org/W2069143585","https://openalex.org/W2095705004","https://openalex.org/W2138108551","https://openalex.org/W2157331557","https://openalex.org/W2171279286","https://openalex.org/W2469952266","https://openalex.org/W2512965516","https://openalex.org/W2809307135","https://openalex.org/W2899457523","https://openalex.org/W2950898568","https://openalex.org/W2953586472","https://openalex.org/W2963351448","https://openalex.org/W2964015378","https://openalex.org/W2964044287","https://openalex.org/W2964926209","https://openalex.org/W2965919199","https://openalex.org/W2986515219","https://openalex.org/W3021402147","https://openalex.org/W3034329572","https://openalex.org/W3080292067","https://openalex.org/W3101707147","https://openalex.org/W3106433415","https://openalex.org/W3199882282","https://openalex.org/W3217142607","https://openalex.org/W4285817843","https://openalex.org/W4295536352","https://openalex.org/W4297733535","https://openalex.org/W4299286960","https://openalex.org/W4307570893","https://openalex.org/W4313887009","https://openalex.org/W4385245566","https://openalex.org/W4386158527","https://openalex.org/W6630221451","https://openalex.org/W6674330103","https://openalex.org/W6680451568","https://openalex.org/W6682889407","https://openalex.org/W6683250468","https://openalex.org/W6690815549","https://openalex.org/W6692935382","https://openalex.org/W6726873649","https://openalex.org/W6745537798"],"related_works":["https://openalex.org/W4307100037","https://openalex.org/W2968745142","https://openalex.org/W2809363009","https://openalex.org/W2348159088","https://openalex.org/W2045871438","https://openalex.org/W4287776258","https://openalex.org/W3027997911","https://openalex.org/W3021430260","https://openalex.org/W4226345073","https://openalex.org/W4384470981"],"abstract_inverted_index":{"Session-based":[0,62],"recommendation":[1,23,81],"is":[2],"a":[3,50,75,102,117,152],"crucial":[4],"task":[5],"aiming":[6],"to":[7,65,78,106,122,140,161],"predict":[8],"users\u2019":[9],"interested":[10],"items":[11,146],"based":[12,90],"only":[13],"on":[14,42,91,167,175],"anonymous":[15],"user":[16],"behaviors.":[17],"Most":[18],"recent":[19],"solutions":[20],"for":[21,61],"session-based":[22],"comprehensively":[24],"consider":[25],"the":[26,34,80,128,135,142,148,158,171,181],"interactive":[27],"information":[28],"of":[29,36,71,145,184],"all":[30,72,92,112],"sessions":[31,73],"but":[32],"bring":[33],"problem":[35],"imbalanced":[37],"positive":[38,163],"and":[39,67,87,164],"negative":[40,165],"samples":[41,166],"model":[43,168],"training.":[44],"In":[45],"this":[46],"paper,":[47],"we":[48],"propose":[49],"novel":[51,153],"approach,":[52],"named":[53],"Attention-enhanced":[54],"Graph":[55],"Neural":[56],"Networks":[57],"with":[58,101],"Global":[59],"Context":[60],"Recommendation":[63],"(AGNN-GC),":[64],"learn":[66,107,123],"merge":[68],"item":[69,109,125,138],"transitions":[70],"in":[74,111,127,147],"cleverer":[76],"way":[77],"enhance":[79,141],"effects.":[82],"AGNN-GC":[83,185],"first":[84],"constructs":[85],"global":[86],"local":[88],"graphs":[89],"training":[93,169],"sequences.":[94],"Next,":[95],"it":[96,115,133],"uses":[97],"graph":[98,118],"convolutional":[99],"networks":[100,120],"session-aware":[103],"attention":[104,119,154],"mechanism":[105],"global-level":[108],"embedding":[110,126,139],"sessions.":[113,130],"Then":[114],"employs":[116],"module":[121],"local-level":[124],"current":[129,149],"After":[131],"that,":[132],"fuses":[134],"learned":[136],"two-level":[137],"feature":[143],"presentations":[144],"session":[150],"by":[151],"mechanism.":[155],"Finally,":[156],"applying":[157],"focal":[159],"loss":[160],"balance":[162],"accomplishes":[170],"prediction.":[172],"Our":[173],"experiments":[174],"three":[176],"real-world":[177],"datasets":[178],"consistently":[179],"show":[180],"superior":[182],"performance":[183],"over":[186],"state-of-the-art":[187],"methods.":[188]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-19T21:40:30.786675","created_date":"2025-10-10T00:00:00"}
