{"id":"https://openalex.org/W4400488181","doi":"https://doi.org/10.1109/tbdata.2024.3426355","title":"Graph Convolutional Networks With Collaborative Feature Fusion for Sequential Recommendation","display_name":"Graph Convolutional Networks With Collaborative Feature Fusion for Sequential Recommendation","publication_year":2024,"publication_date":"2024-07-10","ids":{"openalex":"https://openalex.org/W4400488181","doi":"https://doi.org/10.1109/tbdata.2024.3426355"},"language":"en","primary_location":{"id":"doi:10.1109/tbdata.2024.3426355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2024.3426355","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-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/A5042645332","display_name":"Jianping Gou","orcid":"https://orcid.org/0000-0003-1413-0693"},"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":"Jianping Gou","raw_affiliation_strings":["College of Computer and Information Science, College of Software, Southwest University, Chongqing, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Information Science, College of Software, Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114113451","display_name":"Youhui Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I115592961","display_name":"Jiangsu University","ror":"https://ror.org/03jc41j30","country_code":"CN","type":"education","lineage":["https://openalex.org/I115592961"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youhui Cheng","raw_affiliation_strings":["School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, China","School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, China","institution_ids":["https://openalex.org/I115592961"]},{"raw_affiliation_string":"School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, Jiangsu, China","institution_ids":["https://openalex.org/I115592961"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5074672983","display_name":"Yibing Zhan","orcid":"https://orcid.org/0000-0003-3180-0484"},"institutions":[{"id":"https://openalex.org/I4210103986","display_name":"Jingdong (China)","ror":"https://ror.org/01dkjkq64","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210103986"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yibing Zhan","raw_affiliation_strings":["JD Explore Academy, Beijing, China","JD Explore Academy, China"],"affiliations":[{"raw_affiliation_string":"JD Explore Academy, Beijing, China","institution_ids":["https://openalex.org/I4210103986"]},{"raw_affiliation_string":"JD Explore Academy, China","institution_ids":["https://openalex.org/I4210103986"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085309099","display_name":"Baosheng Yu","orcid":"https://orcid.org/0000-0002-0761-7893"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Baosheng Yu","raw_affiliation_strings":["School of Computer Science, The University of Sydney, Darlington, NSW, Australia"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, The University of Sydney, Darlington, NSW, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028245257","display_name":"Weihua Ou","orcid":"https://orcid.org/0000-0001-5241-7703"},"institutions":[{"id":"https://openalex.org/I154893126","display_name":"Guizhou Normal University","ror":"https://ror.org/02x1pa065","country_code":"CN","type":"education","lineage":["https://openalex.org/I154893126"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Ou","raw_affiliation_strings":["School of Big Data and Computer Science, Guizhou Normal University, Guiyang, China","School of Big Data and Computer Science, Guizhou Normal University, Guiyang, Guizhou, China"],"affiliations":[{"raw_affiliation_string":"School of Big Data and Computer Science, Guizhou Normal University, Guiyang, China","institution_ids":["https://openalex.org/I154893126"]},{"raw_affiliation_string":"School of Big Data and Computer Science, Guizhou Normal University, Guiyang, Guizhou, China","institution_ids":["https://openalex.org/I154893126"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100388188","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0002-5867-9322"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhang","raw_affiliation_strings":["School of Computer Science, Sichuan University, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science, Sichuan University, Chengdu, China","institution_ids":["https://openalex.org/I4210125143","https://openalex.org/I24185976"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5042645332"],"corresponding_institution_ids":["https://openalex.org/I142108993"],"apc_list":null,"apc_paid":null,"fwci":4.0592,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.94301784,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"11","issue":"2","first_page":"735","last_page":"747"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9912999868392944,"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":0.9912999868392944,"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":0.9120000004768372,"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":0.8296364545822144},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5440321564674377},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.48124265670776367},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4349311888217926},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39226478338241577},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.38862869143486023}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8296364545822144},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5440321564674377},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.48124265670776367},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4349311888217926},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39226478338241577},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.38862869143486023},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tbdata.2024.3426355","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tbdata.2024.3426355","pdf_url":null,"source":{"id":"https://openalex.org/S2491400915","display_name":"IEEE Transactions on Big Data","issn_l":"2332-7790","issn":["2332-7790","2372-2096"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Big Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3406750037","display_name":null,"funder_award_id":"61976107","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4363603836","display_name":null,"funder_award_id":"61962010","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7784321418","display_name":null,"funder_award_id":"62262005","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":55,"referenced_works":["https://openalex.org/W2019040312","https://openalex.org/W2171279286","https://openalex.org/W2469952266","https://openalex.org/W2624407581","https://openalex.org/W2625746539","https://openalex.org/W2723293840","https://openalex.org/W2783272285","https://openalex.org/W2807021761","https://openalex.org/W2899457523","https://openalex.org/W2902040508","https://openalex.org/W2945827670","https://openalex.org/W2950703532","https://openalex.org/W2964352502","https://openalex.org/W2965898633","https://openalex.org/W2977404935","https://openalex.org/W2996970889","https://openalex.org/W2997261254","https://openalex.org/W3034169498","https://openalex.org/W3034368386","https://openalex.org/W3035321581","https://openalex.org/W3042006680","https://openalex.org/W3045200674","https://openalex.org/W3097300053","https://openalex.org/W3116048950","https://openalex.org/W3156925821","https://openalex.org/W3164795807","https://openalex.org/W3169207496","https://openalex.org/W3178835722","https://openalex.org/W3193405108","https://openalex.org/W4205091644","https://openalex.org/W4205662443","https://openalex.org/W4210730494","https://openalex.org/W4220909642","https://openalex.org/W4221121670","https://openalex.org/W4224940316","https://openalex.org/W4283065823","https://openalex.org/W4296640362","https://openalex.org/W4306914511","https://openalex.org/W4319300241","https://openalex.org/W4321479942","https://openalex.org/W4322576299","https://openalex.org/W4376118237","https://openalex.org/W4384644330","https://openalex.org/W4384655737","https://openalex.org/W4385270569","https://openalex.org/W4385696611","https://openalex.org/W4385834286","https://openalex.org/W4390345389","https://openalex.org/W6638523607","https://openalex.org/W6680830989","https://openalex.org/W6692935382","https://openalex.org/W6748108687","https://openalex.org/W6779567084","https://openalex.org/W6789174757","https://openalex.org/W7038989634"],"related_works":["https://openalex.org/W4391621807","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391621790","https://openalex.org/W4239306820","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W2947043951","https://openalex.org/W2788292821"],"abstract_inverted_index":{"Sequential":[0],"recommendation":[1,23,57,175,189],"seeks":[2],"to":[3,35,63,120,148],"understand":[4],"user":[5,104,166],"preferences":[6,51,128],"based":[7],"on":[8,171],"their":[9,33],"past":[10],"actions":[11],"and":[12,48,72,125,154],"predict":[13],"future":[14],"interactions":[15],"with":[16,89],"items.":[17],"Recently,":[18],"several":[19],"techniques":[20],"for":[21,32,116],"sequential":[22,174],"have":[24],"emerged,":[25],"primarily":[26],"leveraging":[27],"graph":[28],"convolutional":[29],"networks":[30],"(GCNs)":[31],"ability":[34],"model":[36,181],"relationships":[37],"effectively.":[38],"However,":[39],"real-world":[40],"scenarios":[41],"often":[42],"involve":[43],"sparse":[44],"interactions,":[45],"where":[46],"early":[47,71,124,153],"recent":[49,73,126,155,183],"short-term":[50,74,127,156],"play":[52],"distinct":[53],"roles":[54],"in":[55,138,186],"the":[56,66,98,122,152],"process.":[58],"Consequently,":[59],"vanilla":[60],"GCNs":[61,137],"struggle":[62],"effectively":[64],"capture":[65,121],"explicit":[67],"correlations":[68],"between":[69,151],"these":[70,78,117],"preferences.":[75,157,167],"To":[76,130],"address":[77],"challenges,":[79],"we":[80,134],"introduce":[81],"a":[82,139,144,161],"novel":[83],"approach":[84,159],"termed":[85],"Graph":[86],"Convolutional":[87],"Networks":[88],"Collaborative":[90],"Feature":[91],"Fusion":[92],"(COFF).":[93],"Specifically,":[94],"our":[95,179],"method":[96],"addresses":[97],"issue":[99],"by":[100],"initially":[101],"dividing":[102],"each":[103],"interaction":[105],"sequence":[106],"into":[107],"two":[108,113],"segments.":[109],"We":[110],"then":[111],"construct":[112],"separate":[114],"graphs":[115],"segments,":[118],"aiming":[119],"user's":[123],"independently.":[129],"obtain":[131],"robust":[132],"prediction,":[133],"employ":[135],"multiple":[136],"collaborative":[140],"distillation":[141],"manner,":[142],"incorporating":[143],"feature":[145],"fusion":[146],"module":[147],"establish":[149],"connections":[150],"This":[158],"enables":[160],"more":[162],"precise":[163],"representation":[164],"of":[165,188],"Experimental":[168],"evaluations":[169],"conducted":[170],"five":[172],"popular":[173],"datasets":[176],"demonstrate":[177],"that":[178],"COFF":[180],"outperforms":[182],"state-of-the-art":[184],"methods":[185],"terms":[187],"accuracy.":[190]},"counts_by_year":[{"year":2025,"cited_by_count":5}],"updated_date":"2025-12-23T23:11:35.936235","created_date":"2025-10-10T00:00:00"}