{"id":"https://openalex.org/W4412376863","doi":"https://doi.org/10.1145/3726302.3730251","title":"Squeeze and Excitation: A Weighted Graph Contrastive Learning for Collaborative Filtering","display_name":"Squeeze and Excitation: A Weighted Graph Contrastive Learning for Collaborative Filtering","publication_year":2025,"publication_date":"2025-07-13","ids":{"openalex":"https://openalex.org/W4412376863","doi":"https://doi.org/10.1145/3726302.3730251"},"language":"en","primary_location":{"id":"doi:10.1145/3726302.3730251","doi":"https://doi.org/10.1145/3726302.3730251","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730251","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730251","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730251","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101621051","display_name":"Zheyu Chen","orcid":"https://orcid.org/0009-0003-5779-3523","observed_orcids":["https://orcid.org/0009-0003-5779-3523"]},"institutions":[{"id":"https://openalex.org/I14243506","display_name":"Hong Kong Polytechnic University","ror":"https://ror.org/0030zas98","country_code":"HK","type":"education","lineage":["https://openalex.org/I14243506"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zheyu Chen","raw_affiliation_strings":["The Hong Kong Polytechnic University, Hong Kong SAR, China"],"raw_orcid":"https://orcid.org/0009-0003-5779-3523","affiliations":[{"raw_affiliation_string":"The Hong Kong Polytechnic University, Hong Kong SAR, China","institution_ids":["https://openalex.org/I14243506"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009892151","display_name":"Jinfeng Xu","orcid":"https://orcid.org/0009-0001-7876-3740","observed_orcids":["https://orcid.org/0009-0001-7876-3740"]},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Jinfeng Xu","raw_affiliation_strings":["The University of Hong Kong, Hong Kong SAR, China"],"raw_orcid":"https://orcid.org/0009-0001-7876-3740","affiliations":[{"raw_affiliation_string":"The University of Hong Kong, Hong Kong SAR, China","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112325788","display_name":"Yutong Wei","orcid":"https://orcid.org/0009-0006-5444-8005","observed_orcids":["https://orcid.org/0009-0006-5444-8005"]},"institutions":[{"id":"https://openalex.org/I139660479","display_name":"Central South University","ror":"https://ror.org/00f1zfq44","country_code":"CN","type":"education","lineage":["https://openalex.org/I139660479"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yutong Wei","raw_affiliation_strings":["Central South University, Changsha, China"],"raw_orcid":"https://orcid.org/0009-0006-5444-8005","affiliations":[{"raw_affiliation_string":"Central South University, Changsha, China","institution_ids":["https://openalex.org/I139660479"]}]},{"author_position":"last","author":{"id":null,"display_name":"Ziyue Peng","orcid":"https://orcid.org/0009-0000-3811-4570","observed_orcids":["https://orcid.org/0009-0000-3811-4570"]},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Ziyue Peng","raw_affiliation_strings":["University of Macau, Macau SAR, China"],"raw_orcid":"https://orcid.org/0009-0000-3811-4570","affiliations":[{"raw_affiliation_string":"University of Macau, Macau SAR, China","institution_ids":["https://openalex.org/I204512498"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":18.6584,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.99447477,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"2769","last_page":"2773"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.9994999766349792,"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":0.9994999766349792,"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":0.00019999999494757503,"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":0.0,"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/graph-contrastive-learning","display_name":"graph contrastive learning","score":0.9070000052452087},{"id":"https://openalex.org/keywords/squeeze-and-excitation","display_name":"squeeze-and-excitation","score":0.8669999837875366},{"id":"https://openalex.org/keywords/collaborative-filtering","display_name":"collaborative filtering","score":0.9900000095367432},{"id":"https://openalex.org/keywords/recommender-systems","display_name":"recommender systems","score":0.9229999780654907},{"id":"https://openalex.org/keywords/graph-convolutional-networks","display_name":"graph convolutional networks","score":0.8679999709129333},{"id":"https://openalex.org/keywords/user-item-bipartite-graph","display_name":"user-item bipartite graph","score":0.9259999990463257},{"id":"https://openalex.org/keywords/data-sparsity","display_name":"data sparsity","score":0.7080000042915344},{"id":"https://openalex.org/keywords/self-supervised-learning","display_name":"self-supervised learning","score":0.9229999780654907}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6589388847351074},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5222290754318237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48324379324913025},{"id":"https://openalex.org/C83581075","wikidata":"https://www.wikidata.org/wiki/Q1361503","display_name":"Excitation","level":2,"score":0.4330500364303589},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3896549344062805},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2864387631416321},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11746475100517273},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0819278359413147}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3726302.3730251","doi":"https://doi.org/10.1145/3726302.3730251","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730251","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730251","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2504.04443","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2504.04443","pdf_url":"https://arxiv.org/pdf/2504.04443","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2504.04443","doi":"https://doi.org/10.48550/arxiv.2504.04443","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2504.04443","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.1145/3726302.3730251","doi":"https://doi.org/10.1145/3726302.3730251","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3726302.3730251","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3726302.3730251","source":{"id":"https://openalex.org/S4363608773","display_name":"International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":"Proceedings of the 48th International ACM SIGIR Conference on Research and Development in Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4412376863.pdf","grobid_xml":"https://content.openalex.org/works/W4412376863.grobid-xml"},"referenced_works_count":21,"referenced_works":["https://openalex.org/W2027731328","https://openalex.org/W2069065514","https://openalex.org/W2069870183","https://openalex.org/W2605350416","https://openalex.org/W2752782242","https://openalex.org/W2913754224","https://openalex.org/W2945827670","https://openalex.org/W2982108874","https://openalex.org/W3045200674","https://openalex.org/W3094605801","https://openalex.org/W3211143493","https://openalex.org/W4220909642","https://openalex.org/W4372279027","https://openalex.org/W4385270524","https://openalex.org/W4391376193","https://openalex.org/W4399486943","https://openalex.org/W4400529753","https://openalex.org/W4408354021","https://openalex.org/W4409657429","https://openalex.org/W4412376859","https://openalex.org/W6600708310"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Contrastive":[0,109],"Learning":[1,110],"(CL)":[2],"has":[3,70],"recently":[4],"emerged":[5],"as":[6],"a":[7,47,106,115,132],"powerful":[8],"technique":[9],"in":[10,46,77,99],"recommendation":[11],"systems,":[12],"particularly":[13],"for":[14,67],"its":[15],"capability":[16],"to":[17,24,93,137,176],"harness":[18],"self-supervised":[19],"signals":[20],"from":[21],"perturbed":[22,33,44,68,144],"views":[23,34,45,69],"mitigate":[25],"the":[26,36,63,82,90,122,125,140,143,148,156],"data":[27],"sparsity":[28],"problem.The":[29],"process":[30],"of":[31,35,85,124,142,158],"constructing":[32],"user-item":[37],"bipartite":[38],"graph":[39,48,54],"and":[40,134,154],"performing":[41],"CL":[42],"between":[43],"convolutional":[49],"network":[50,136],"(GCN)":[51],"is":[52,81],"called":[53],"contrastive":[55],"learning":[56],"(GCL).Although":[57],"existing":[58,78],"GCL-based":[59,79],"models":[60,80],"are":[61],"effective,":[62],"weight":[64,139],"assignment":[65],"method":[66],"not":[71],"been":[72],"fully":[73],"explored.A":[74],"critical":[75],"problem":[76,88],"irrational":[83],"allocation":[84],"feature":[86],"attention.This":[87],"limits":[89],"model's":[91,149],"ability":[92],"effectively":[94],"leverage":[95],"crucial":[96,152],"features,":[97],"resulting":[98],"suboptimal":[100],"performance.To":[101],"address":[102],"this,":[103],"we":[104],"propose":[105],"Weighted":[107],"Graph":[108],"framework":[111],"(WeightedGCL).Specifically,":[112],"WeightedGCL":[113,130,146],"applies":[114],"robust":[116],"perturbation":[117],"strategy,":[118],"which":[119],"perturbs":[120],"only":[121],"view":[123],"final":[126],"GCN":[127],"layer.In":[128],"addition,":[129],"incorporates":[131],"squeeze":[133],"excitation":[135],"dynamically":[138],"features":[141,153],"views.Our":[145],"strengthens":[147],"focus":[150],"on":[151,163],"reduces":[155],"impact":[157],"less":[159],"relevant":[160],"information.Extensive":[161],"experiments":[162],"widely":[164],"used":[165],"datasets":[166],"demonstrate":[167],"that":[168],"our":[169],"Weight-edGCL":[170],"achieves":[171],"significant":[172],"accuracy":[173],"improvements":[174],"compared":[175],"competitive":[177],"baselines.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":7}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}
