{"id":"https://openalex.org/W4396886548","doi":"https://doi.org/10.1109/access.2024.3400788","title":"Hierarchically Coupled View-Crossing Contrastive Learning for Knowledge Enhanced Recommendation","display_name":"Hierarchically Coupled View-Crossing Contrastive Learning for Knowledge Enhanced Recommendation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4396886548","doi":"https://doi.org/10.1109/access.2024.3400788"},"language":"en","primary_location":{"id":"doi:10.1109/access.2024.3400788","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3400788","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10530300.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":null,"license_id":null,"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/ielx7/6287639/6514899/10530300.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040428922","display_name":"Shuai Chen","orcid":"https://orcid.org/0009-0009-4474-6481"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuai Chen","raw_affiliation_strings":["State Key Laboratory of Software Development Environment, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0009-4474-6481","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Development Environment, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036786337","display_name":"Zhoujun Li","orcid":"https://orcid.org/0000-0002-9603-9713"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhoujun Li","raw_affiliation_strings":["State Key Laboratory of Software Development Environment, Beihang University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9603-9713","affiliations":[{"raw_affiliation_string":"State Key Laboratory of Software Development Environment, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":1.9187,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.88325755,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"12","issue":null,"first_page":"75532","last_page":"75541"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9984999895095825,"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":0.9984999895095825,"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":0.9957000017166138,"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/T13702","display_name":"Machine Learning in Healthcare","score":0.9753000140190125,"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":0.8554622530937195},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.6132272481918335},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.5336651802062988},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.5312172174453735},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5001916885375977},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4877951443195343},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.45495596528053284},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35994553565979004},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3555152714252472}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8554622530937195},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.6132272481918335},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.5336651802062988},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.5312172174453735},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5001916885375977},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4877951443195343},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.45495596528053284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35994553565979004},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3555152714252472},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2024.3400788","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3400788","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10530300.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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:afc37208d5ac488aaa97408ca2968a76","is_oa":true,"landing_page_url":"https://doaj.org/article/afc37208d5ac488aaa97408ca2968a76","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 12, Pp 75532-75541 (2024)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2024.3400788","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2024.3400788","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10530300.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":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2323930268","display_name":null,"funder_award_id":"U1636211","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3714348066","display_name":null,"funder_award_id":"62276017","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7104496898","display_name":"\u793e\u533a\u95ee\u7b54\u7cfb\u7edf\u5173\u952e\u6280\u672f\u7814\u7a76","funder_award_id":"61672081","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8995363059","display_name":null,"funder_award_id":"SKLSDE-2021ZX-18","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":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4396886548.pdf"},"referenced_works_count":51,"referenced_works":["https://openalex.org/W1677182931","https://openalex.org/W2140310134","https://openalex.org/W2509893387","https://openalex.org/W2605350416","https://openalex.org/W2624407581","https://openalex.org/W2772021946","https://openalex.org/W2792839191","https://openalex.org/W2793768763","https://openalex.org/W2807021761","https://openalex.org/W2884134047","https://openalex.org/W2894039884","https://openalex.org/W2907349915","https://openalex.org/W2911778742","https://openalex.org/W2912351665","https://openalex.org/W2913560138","https://openalex.org/W2945623882","https://openalex.org/W2945827670","https://openalex.org/W2949687195","https://openalex.org/W2951050019","https://openalex.org/W2963085847","https://openalex.org/W2963707260","https://openalex.org/W2963869731","https://openalex.org/W2964015378","https://openalex.org/W2966349618","https://openalex.org/W2982019227","https://openalex.org/W2985165384","https://openalex.org/W2994717084","https://openalex.org/W3034364571","https://openalex.org/W3045200674","https://openalex.org/W3088777230","https://openalex.org/W3094605801","https://openalex.org/W3097982973","https://openalex.org/W3098087397","https://openalex.org/W3098923689","https://openalex.org/W3100278010","https://openalex.org/W3100848837","https://openalex.org/W3104030692","https://openalex.org/W3106439716","https://openalex.org/W3129482887","https://openalex.org/W3153325943","https://openalex.org/W3155919942","https://openalex.org/W3171249018","https://openalex.org/W3208227120","https://openalex.org/W4224914537","https://openalex.org/W4225412853","https://openalex.org/W4297733535","https://openalex.org/W4321480047","https://openalex.org/W4383604692","https://openalex.org/W6680830989","https://openalex.org/W6682948231","https://openalex.org/W6726873649"],"related_works":["https://openalex.org/W2770593030","https://openalex.org/W3154990682","https://openalex.org/W2560201613","https://openalex.org/W2171975302","https://openalex.org/W2022352247","https://openalex.org/W2488129135","https://openalex.org/W4312219546","https://openalex.org/W2787993192","https://openalex.org/W2377538627","https://openalex.org/W2107220315"],"abstract_inverted_index":{"Knowledge":[0],"enhanced":[1,23,116],"recommendation":[2,16,24,117],"algorithms":[3],"focus":[4],"on":[5,194],"how":[6],"to":[7,14,58,118,162],"leverage":[8],"auxiliary":[9],"information":[10,60,130],"from":[11,61],"knowledge":[12,22,48,97,115,128],"graphs":[13,46],"enhance":[15],"performance.":[17],"However,":[18],"existing":[19],"methods":[20],"for":[21,114,170],"often":[25,39],"overlook":[26],"the":[27,30,59,71,74,88,93,120,144,149,174,181,187,208,212,220],"issues":[28],"of":[29,33,53,73,82,96,134,143,184,214,222],"non-uniform":[31],"distribution":[32,52],"task-relevant":[34],"information:":[35],"(1)":[36],"Item":[37],"nodes":[38,55],"have":[40],"neighbors":[41],"unevenly":[42],"distributed":[43],"across":[44],"interaction":[45],"and":[47,137,177,211],"graphs.":[49],"This":[50],"uneven":[51],"neighbor":[54],"might":[56],"lead":[57],"certain":[62],"sources":[63],"being":[64],"ignored":[65],"during":[66],"message":[67,135],"passing,":[68,136],"thereby":[69],"reducing":[70],"quality":[72],"learned":[75,146],"node":[76,151],"embeddings.":[77],"(2)":[78],"The":[79],"implicit":[80],"inclusion":[81],"noise":[83,185],"within":[84],"graph":[85,98,129,197],"data":[86],"exacerbates":[87],"aforementioned":[89],"issues,":[90],"further":[91],"hindering":[92],"effective":[94],"utilization":[95],"information.":[99],"In":[100,153],"this":[101],"paper,":[102],"we":[103,125,155],"introduce":[104],"a":[105,140,157],"novel":[106],"algorithm":[107],"called":[108],"hierarchically":[109,147],"coupled":[110],"view-crossing":[111,158],"contrastive":[112,159,166,189],"learning":[113,160,167,190],"address":[119],"challenges":[121],"mentioned":[122],"above.":[123],"Specifically,":[124],"controllably":[126],"couple":[127],"into":[131],"each":[132],"layer":[133],"then":[138],"use":[139],"weighted":[141],"sum":[142],"embeddings":[145],"as":[148],"final":[150],"representation.":[152],"addition,":[154],"devised":[156],"approach":[161],"construct":[163],"two":[164],"additional":[165],"loss":[168],"functions":[169],"joint":[171],"training":[172],"with":[173],"main":[175],"task":[176],"more":[178],"effectively":[179],"mitigate":[180],"adverse":[182],"impact":[183],"than":[186,207],"traditional":[188],"paradigms.":[191],"Extensive":[192],"experiments":[193,215],"three":[195],"real-world":[196],"datasets":[198],"show":[199],"that":[200],"our":[201,223],"proposed":[202],"model":[203],"performs":[204],"significantly":[205],"better":[206],"state-of-the-art":[209],"baselines":[210],"results":[213],"involving":[216],"adversarial":[217],"samples":[218],"indicate":[219],"robustness":[221],"model.":[224]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}
