{"id":"https://openalex.org/W4312467948","doi":"https://doi.org/10.1109/ijcnn55064.2022.9891894","title":"Global Context-Aware Graph Neural Networks for Session-based Recommendation","display_name":"Global Context-Aware Graph Neural Networks for Session-based Recommendation","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4312467948","doi":"https://doi.org/10.1109/ijcnn55064.2022.9891894"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn55064.2022.9891894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9891894","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"2022 International Joint Conference on Neural Networks (IJCNN)","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/A5100698753","display_name":"Mingfeng Wang","orcid":"https://orcid.org/0000-0001-6551-0325"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Mingfeng Wang","raw_affiliation_strings":["School of Computer Science, Wuhan University,Wuhan,China","School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University,Wuhan,China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100336998","display_name":"Jing Li","orcid":"https://orcid.org/0000-0002-8044-2284"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["School of Computer Science, Wuhan University,Wuhan,China","School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University,Wuhan,China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103268548","display_name":"Jun Chang","orcid":"https://orcid.org/0000-0002-3594-9879"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Chang","raw_affiliation_strings":["School of Computer Science, Wuhan University,Wuhan,China","School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University,Wuhan,China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101700523","display_name":"Donghua Liu","orcid":"https://orcid.org/0000-0002-8098-7655"},"institutions":[{"id":"https://openalex.org/I4210100221","display_name":"China Waterborne Transport Research Institute","ror":"https://ror.org/013kb0k13","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210100221"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Donghua Liu","raw_affiliation_strings":["China Waterborne Transport Research Institute,Information Center,Beijing,China","Information Center, China Waterborne Transport Research Institute, Beijing, China"],"affiliations":[{"raw_affiliation_string":"China Waterborne Transport Research Institute,Information Center,Beijing,China","institution_ids":["https://openalex.org/I4210100221"]},{"raw_affiliation_string":"Information Center, China Waterborne Transport Research Institute, Beijing, China","institution_ids":["https://openalex.org/I4210100221"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101960812","display_name":"Chenyan Zhang","orcid":"https://orcid.org/0000-0002-2858-5675"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyan Zhang","raw_affiliation_strings":["School of Computer Science, Wuhan University,Wuhan,China","School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University,Wuhan,China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028597717","display_name":"Xiaosai Huang","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaosai Huang","raw_affiliation_strings":["School of Computer Science, Wuhan University,Wuhan,China","School of Computer Science, Wuhan University, Wuhan, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University,Wuhan,China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100698753"],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.23230858,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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":0.9972000122070312,"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/T12101","display_name":"Advanced Bandit Algorithms Research","score":0.9822999835014343,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8577713966369629},{"id":"https://openalex.org/keywords/session","display_name":"Session (web analytics)","score":0.8379616141319275},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.7621716260910034},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5466409921646118},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4660924971103668},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.44621166586875916},{"id":"https://openalex.org/keywords/recommender-system","display_name":"Recommender system","score":0.43135374784469604},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.42618024349212646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41646450757980347},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4160849153995514},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.22546008229255676},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.21354752779006958}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8577713966369629},{"id":"https://openalex.org/C2779182362","wikidata":"https://www.wikidata.org/wiki/Q17126187","display_name":"Session (web analytics)","level":2,"score":0.8379616141319275},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.7621716260910034},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5466409921646118},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4660924971103668},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.44621166586875916},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.43135374784469604},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42618024349212646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41646450757980347},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4160849153995514},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.22546008229255676},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.21354752779006958},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn55064.2022.9891894","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn55064.2022.9891894","pdf_url":null,"source":{"id":"https://openalex.org/S4363607707","display_name":"2022 International Joint Conference on Neural Networks (IJCNN)","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":"2022 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3507083598","display_name":null,"funder_award_id":"61822113","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7986140881","display_name":null,"funder_award_id":"2018CFA050","funder_id":"https://openalex.org/F4320322186","funder_display_name":"Natural Science Foundation of Hubei Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322186","display_name":"Natural Science Foundation of Hubei Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1970269368","https://openalex.org/W2027287130","https://openalex.org/W2171279286","https://openalex.org/W2807942528","https://openalex.org/W2809307135","https://openalex.org/W2842511635","https://openalex.org/W2899457523","https://openalex.org/W2909882940","https://openalex.org/W2953586472","https://openalex.org/W2963703618","https://openalex.org/W2964044287","https://openalex.org/W2964926209","https://openalex.org/W2986515219","https://openalex.org/W3004835491","https://openalex.org/W3034329572","https://openalex.org/W3035666843","https://openalex.org/W3090516735","https://openalex.org/W3094605801","https://openalex.org/W3101707147","https://openalex.org/W3153325943","https://openalex.org/W3173365306","https://openalex.org/W3185693672","https://openalex.org/W3206604724","https://openalex.org/W4220941681","https://openalex.org/W4297808394","https://openalex.org/W4299286960","https://openalex.org/W6692935382","https://openalex.org/W6743446608","https://openalex.org/W6758623387","https://openalex.org/W6765016166","https://openalex.org/W6772762736"],"related_works":["https://openalex.org/W17155033","https://openalex.org/W3207760230","https://openalex.org/W1496222301","https://openalex.org/W4312814274","https://openalex.org/W1590307681","https://openalex.org/W2536018345","https://openalex.org/W4285370786","https://openalex.org/W2296488620","https://openalex.org/W2358353312","https://openalex.org/W2353836703"],"abstract_inverted_index":{"Session-based":[0],"recommendation,":[1,83],"which":[2,108],"uses":[3],"the":[4,25,62,79,110,135,139,153,200,206],"interactive":[5],"information":[6,67],"of":[7,27,202],"anonymous":[8],"users":[9],"in":[10,32,78],"a":[11,98,149,166],"period":[12],"to":[13,37,54,60,86,122,157,174,191],"predict":[14],"user":[15,90,124,129,146,193],"preferences,":[16],"has":[17],"attracted":[18],"extensive":[19],"attention.":[20],"Existing":[21],"methods":[22,52,71],"mainly":[23],"exploit":[24,55],"strengths":[26],"graph":[28],"neural":[29],"networks":[30],"(GNNs)":[31],"capturing":[33],"structured":[34],"data":[35],"features":[36],"model":[38,204],"complex":[39],"item":[40],"transitions":[41],"for":[42,81],"recommendations.":[43],"However,":[44],"there":[45],"still":[46],"remain":[47],"some":[48,70],"challenges:":[49],"1)":[50],"many":[51],"neglect":[53],"cross-session":[56,113,136,150],"interactions":[57],"and":[58,65,112,116,138],"fail":[59],"integrate":[61],"latent":[63],"intra-":[64],"inter-session":[66],"effectively.":[68],"2)":[69],"barely":[72],"explore":[73],"fine-grained":[74,118,176],"contextual":[75,120,177],"factors":[76,121],"underlying":[77],"sessions":[80],"session-based":[82],"thus":[84],"failing":[85],"capture":[87],"more":[88],"comprehensive":[89],"preferences.":[91,125,194],"To":[92],"solve":[93],"these":[94],"issues,":[95],"we":[96,184],"propose":[97],"novel":[99],"method":[100],"called":[101],"Global":[102],"Context-Aware":[103],"Graph":[104,169],"Neural":[105,170],"Networks":[106],"(GCA-GNN)":[107],"captures":[109,117],"local-session":[111,140,163],"preferences":[114,130,147,161],"respectively,":[115],"global":[119],"complement":[123],"Specifically,":[126],"GCA-GNN":[127],"models":[128],"from":[131,148,162],"two":[132],"different":[133],"views:":[134],"view":[137],"view.":[141],"The":[142],"former":[143],"learns":[144],"collaborative":[145],"graph,":[151],"while":[152],"latter":[154],"is":[155,172],"designed":[156],"learn":[158],"users'":[159],"personal":[160],"graphs.":[164],"Furthermore,":[165],"context-aware":[167],"Capsule":[168],"Network":[171],"employed":[173],"extract":[175],"factors,":[178],"serving":[179],"as":[180],"complementary":[181],"information.":[182],"And":[183],"introduce":[185],"an":[186],"auxiliary":[187],"self-supervised":[188],"learning":[189],"task":[190],"enhance":[192],"Experiments":[195],"on":[196],"benchmark":[197],"datasets":[198],"demonstrate":[199],"strength":[201],"our":[203],"over":[205],"state-of-the-art":[207],"methods.":[208]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}