{"id":"https://openalex.org/W4393191804","doi":"https://doi.org/10.1145/3653976","title":"Dual Homogeneity Hypergraph Motifs with Cross-view Contrastive Learning for Multiple Social Recommendations","display_name":"Dual Homogeneity Hypergraph Motifs with Cross-view Contrastive Learning for Multiple Social Recommendations","publication_year":2024,"publication_date":"2024-03-26","ids":{"openalex":"https://openalex.org/W4393191804","doi":"https://doi.org/10.1145/3653976"},"language":"en","primary_location":{"id":"doi:10.1145/3653976","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3653976","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3653976","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3653976","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067493375","display_name":"Jiadi Han","orcid":"https://orcid.org/0000-0001-6276-6691"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiadi Han","raw_affiliation_strings":["South China University of Technology,  Guangzhou, China","South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-6276-6691","affiliations":[{"raw_affiliation_string":"South China University of Technology,  Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044185120","display_name":"Yufei Tang","orcid":"https://orcid.org/0000-0002-6915-4468"},"institutions":[{"id":"https://openalex.org/I63772739","display_name":"Florida Atlantic University","ror":"https://ror.org/05p8w6387","country_code":"US","type":"education","lineage":["https://openalex.org/I63772739"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yufei Tang","raw_affiliation_strings":["Florida Atlantic University, Boca Raton, USA","Florida Atlantic University, Boca Raton, FL, USA"],"raw_orcid":"https://orcid.org/0000-0002-6915-4468","affiliations":[{"raw_affiliation_string":"Florida Atlantic University, Boca Raton, USA","institution_ids":["https://openalex.org/I63772739"]},{"raw_affiliation_string":"Florida Atlantic University, Boca Raton, FL, USA","institution_ids":["https://openalex.org/I63772739"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002411381","display_name":"Qian Tao","orcid":"https://orcid.org/0000-0001-7313-2109"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qian Tao","raw_affiliation_strings":["South China University of Technology, Guangzhou, China and Pazhou Lab,  Guangzhou, China","South China University of Technology, Guangzhou, China and Pazhou Lab, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-7313-2109","affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, China and Pazhou Lab,  Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"South China University of Technology, Guangzhou, China and Pazhou Lab, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053329195","display_name":"Yuhan Xia","orcid":"https://orcid.org/0000-0002-2994-0149"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhan Xia","raw_affiliation_strings":["South China University of Technology,  Guangzhou, China","South China University of Technology, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2994-0149","affiliations":[{"raw_affiliation_string":"South China University of Technology,  Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5106975888","display_name":"Liming Zhang","orcid":"https://orcid.org/0009-0001-9827-7766"},"institutions":[{"id":"https://openalex.org/I1456306","display_name":"North China University of Technology","ror":"https://ror.org/01nky7652","country_code":"CN","type":"education","lineage":["https://openalex.org/I1456306"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liming Zhang","raw_affiliation_strings":["North China University of Technology,  Beijing, China","North China University of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-9827-7766","affiliations":[{"raw_affiliation_string":"North China University of Technology,  Beijing, China","institution_ids":["https://openalex.org/I1456306"]},{"raw_affiliation_string":"North China University of Technology, Beijing, China","institution_ids":["https://openalex.org/I1456306"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.1166,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.9537465,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":"18","issue":"6","first_page":"1","last_page":"24"},"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":0.9943000078201294,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9483000040054321,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.7232613563537598},{"id":"https://openalex.org/keywords/dual","display_name":"Dual (grammatical number)","score":0.5740309953689575},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5177849531173706},{"id":"https://openalex.org/keywords/homogeneity","display_name":"Homogeneity (statistics)","score":0.5130199790000916},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4937494695186615},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3873702585697174},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3255913257598877},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3046956956386566},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29782700538635254},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.19057685136795044},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.13452288508415222}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.7232613563537598},{"id":"https://openalex.org/C2780980858","wikidata":"https://www.wikidata.org/wiki/Q110022","display_name":"Dual (grammatical number)","level":2,"score":0.5740309953689575},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5177849531173706},{"id":"https://openalex.org/C142259097","wikidata":"https://www.wikidata.org/wiki/Q5891314","display_name":"Homogeneity (statistics)","level":2,"score":0.5130199790000916},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4937494695186615},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3873702585697174},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3255913257598877},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3046956956386566},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29782700538635254},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.19057685136795044},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.13452288508415222},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3653976","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3653976","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3653976","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3653976","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3653976","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3653976","source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.6000000238418579}],"awards":[{"id":"https://openalex.org/G4933608124","display_name":null,"funder_award_id":"2022YFC3006401","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G5718940420","display_name":null,"funder_award_id":"62276101","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"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4393191804.pdf","grobid_xml":"https://content.openalex.org/works/W4393191804.grobid-xml"},"referenced_works_count":54,"referenced_works":["https://openalex.org/W1994389483","https://openalex.org/W2101409192","https://openalex.org/W2112008792","https://openalex.org/W2119825970","https://openalex.org/W2135598826","https://openalex.org/W2144487656","https://openalex.org/W2153624566","https://openalex.org/W2244405900","https://openalex.org/W2535170495","https://openalex.org/W2596701210","https://openalex.org/W2605350416","https://openalex.org/W2608239929","https://openalex.org/W2624431344","https://openalex.org/W2800517790","https://openalex.org/W2807021761","https://openalex.org/W2892880750","https://openalex.org/W2912903380","https://openalex.org/W2914721378","https://openalex.org/W2945827670","https://openalex.org/W2963146368","https://openalex.org/W2986416218","https://openalex.org/W3015616869","https://openalex.org/W3032898959","https://openalex.org/W3042856524","https://openalex.org/W3045200674","https://openalex.org/W3080566854","https://openalex.org/W3095937012","https://openalex.org/W3100278010","https://openalex.org/W3100324210","https://openalex.org/W3100848837","https://openalex.org/W3102793640","https://openalex.org/W3114652457","https://openalex.org/W3117298090","https://openalex.org/W3153325943","https://openalex.org/W3153673236","https://openalex.org/W3154246858","https://openalex.org/W3155496675","https://openalex.org/W3155936517","https://openalex.org/W3156028762","https://openalex.org/W3158371160","https://openalex.org/W3170682786","https://openalex.org/W3186710985","https://openalex.org/W3198760092","https://openalex.org/W3204479763","https://openalex.org/W3207066264","https://openalex.org/W3211072770","https://openalex.org/W4205568429","https://openalex.org/W4213174824","https://openalex.org/W4220909642","https://openalex.org/W4224983022","https://openalex.org/W4226033575","https://openalex.org/W4284666445","https://openalex.org/W4284701295","https://openalex.org/W4294558607"],"related_works":["https://openalex.org/W4376608589","https://openalex.org/W3138003926","https://openalex.org/W4300037846","https://openalex.org/W1630514295","https://openalex.org/W1537073411","https://openalex.org/W2963081352","https://openalex.org/W4376608938","https://openalex.org/W4288275998","https://openalex.org/W2472555608","https://openalex.org/W4214498971"],"abstract_inverted_index":{"Social":[0],"relations":[1,23,59,173,193,231],"are":[2,26,43,186,213],"often":[3,95],"used":[4,31,214],"as":[5,202],"auxiliary":[6,204],"information":[7],"to":[8,46,56,99,110,166,189,206,215,228,238],"address":[9,139],"data":[10],"sparsity":[11],"and":[12,28,42,118,161,177,232],"cold-start":[13],"issues":[14],"in":[15,142],"social":[16,22,67,78,85,153,159,172],"recommendations.":[17,154,258],"In":[18],"the":[19,71,81,91,122,132,168,191,209,217,220,234,240,253],"real":[20],"world,":[21],"among":[24],"users":[25,111],"complex":[27],"diverse.":[29],"Widely":[30],"graph":[32],"neural":[33],"networks":[34,183],"(GNNs)":[35],"can":[36],"only":[37],"model":[38,57,190],"pairwise":[39],"node":[40],"relationships":[41,86],"not":[44],"conducive":[45],"exploring":[47],"higher-order":[48],"connectivity,":[49],"while":[50],"hypergraph":[51],"provides":[52],"a":[53,75,147],"natural":[54],"way":[55],"high-order":[58,192],"between":[60,116,135,194],"nodes.":[61,195],"However,":[62],"recent":[63],"studies":[64],"show":[65],"that":[66,112,247],"recommendations":[68,79],"still":[69],"face":[70],"following":[72],"challenges:":[73],"1)":[74],"majority":[76],"of":[77,83,170,219],"ignore":[80],"impact":[82,169],"multifaceted":[84],"on":[87,174,256],"user":[88,175],"preferences;":[89],"2)":[90],"item":[92,162,179],"homogeneity":[93,157,160],"is":[94,164,200],"neglected,":[96],"mainly":[97],"referring":[98],"items":[100],"with":[101,184],"similar":[102,106],"static":[103],"attributes":[104],"have":[105],"attractiveness":[107],"when":[108],"exposed":[109],"indicating":[113],"hidden":[114],"links":[115],"items;":[117],"3)":[119],"directly":[120],"combining":[121],"representations":[123],"learned":[124],"from":[125],"different":[126,136],"independent":[127],"views":[128],"cannot":[129],"fully":[130],"exploit":[131],"potential":[133],"connections":[134],"views.":[137],"To":[138],"these":[140],"challenges,":[141],"this":[143],"article,":[144],"we":[145,224],"propose":[146],"novel":[148],"method":[149,250],"DH-HGCN++":[150],"for":[151],"multiple":[152],"Specifically,":[155],"dual":[156],"(i.e.,":[158],"homogeneity)":[163],"introduced":[165],"mine":[167],"diverse":[171],"preferences":[176],"enrich":[178],"representations.":[180],"Hypergraph":[181],"convolution":[182],"motifs":[185],"further":[187],"exploited":[188],"Finally,":[196],"cross-view":[197],"contrastive":[198],"learning":[199],"proposed":[201,221,249],"an":[203],"task":[205],"jointly":[207],"optimize":[208],"DH-HGCN++.":[210],"Real-world":[211],"datasets":[212],"validate":[216],"effectiveness":[218],"model,":[222],"where":[223],"use":[225],"sentiment":[226],"analysis":[227],"extract":[229],"comment":[230],"employ":[233],"k-means":[235],"clustering":[236],"algorithm":[237],"construct":[239],"item-item":[241],"correlation":[242],"graph.":[243],"Experiment":[244],"results":[245],"demonstrate":[246],"our":[248],"consistently":[251],"outperforms":[252],"state-of-the-art":[254],"baselines":[255],"Top-N":[257]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
