{"id":"https://openalex.org/W7127704411","doi":"https://doi.org/10.1145/3793862","title":"ProGraph: Graph Prompt Tuning with Knowledge-aware Contrastive Learning for Recommendation","display_name":"ProGraph: Graph Prompt Tuning with Knowledge-aware Contrastive Learning for Recommendation","publication_year":2026,"publication_date":"2026-02-04","ids":{"openalex":"https://openalex.org/W7127704411","doi":"https://doi.org/10.1145/3793862"},"language":"en","primary_location":{"id":"doi:10.1145/3793862","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3793862","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"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 Multimedia Computing, Communications, and Applications","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/A5069846690","display_name":"Chuyuan Wei","orcid":null},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chuyuan Wei","raw_affiliation_strings":["Beijing University of Civil Engineering and Architecture, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0352-3002","affiliations":[{"raw_affiliation_string":"Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124986587","display_name":"Anning He","orcid":null},"institutions":[{"id":"https://openalex.org/I62853816","display_name":"Beijing University of Civil Engineering and Architecture","ror":"https://ror.org/02yj0p855","country_code":"CN","type":"education","lineage":["https://openalex.org/I62853816"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anning He","raw_affiliation_strings":["Beijing University of Civil Engineering and Architecture, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0004-1716-0673","affiliations":[{"raw_affiliation_string":"Beijing University of Civil Engineering and Architecture, Beijing, China","institution_ids":["https://openalex.org/I62853816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5092728836","display_name":"Shengda Zhuo","orcid":null},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengda Zhuo","raw_affiliation_strings":["Jinan University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5610-005X","affiliations":[{"raw_affiliation_string":"Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Changdong Wang","orcid":"https://orcid.org/0000-0001-5972-559X"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changdong Wang","raw_affiliation_strings":["Sun Yat-Sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5972-559X","affiliations":[{"raw_affiliation_string":"Sun Yat-Sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"last","author":{"id":null,"display_name":"Shuqiang Huang","orcid":"https://orcid.org/0000-0001-9551-022X"},"institutions":[{"id":"https://openalex.org/I159948400","display_name":"Jinan University","ror":"https://ror.org/02xe5ns62","country_code":"CN","type":"education","lineage":["https://openalex.org/I159948400"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuqiang Huang","raw_affiliation_strings":["Jinan University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-9551-022X","affiliations":[{"raw_affiliation_string":"Jinan University, Guangzhou, China","institution_ids":["https://openalex.org/I159948400"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.09338218,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"4","first_page":"1","last_page":"26"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10203","display_name":"Recommender Systems and Techniques","score":0.6970999836921692,"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":0.6970999836921692,"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":0.23399999737739563,"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":0.013899999670684338,"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/recommender-system","display_name":"Recommender system","score":0.5681999921798706},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5526000261306763},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.47920000553131104},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.43560001254081726},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.38449999690055847},{"id":"https://openalex.org/keywords/transferability","display_name":"Transferability","score":0.36739999055862427},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.3653999865055084}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8970000147819519},{"id":"https://openalex.org/C557471498","wikidata":"https://www.wikidata.org/wiki/Q554950","display_name":"Recommender system","level":2,"score":0.5681999921798706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.564300000667572},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5526000261306763},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.47920000553131104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46709999442100525},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.43560001254081726},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.414000004529953},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.38449999690055847},{"id":"https://openalex.org/C61272859","wikidata":"https://www.wikidata.org/wiki/Q7834031","display_name":"Transferability","level":3,"score":0.36739999055862427},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.3653999865055084},{"id":"https://openalex.org/C101468663","wikidata":"https://www.wikidata.org/wiki/Q1620158","display_name":"Modular design","level":2,"score":0.35510000586509705},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.3481000065803528},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.30379998683929443},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30239999294281006},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2964000105857849},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.28700000047683716},{"id":"https://openalex.org/C42355184","wikidata":"https://www.wikidata.org/wiki/Q1361088","display_name":"Matrix decomposition","level":3,"score":0.2757999897003174},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.2743000090122223},{"id":"https://openalex.org/C170133592","wikidata":"https://www.wikidata.org/wiki/Q1806883","display_name":"Latent semantic analysis","level":2,"score":0.25999999046325684}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3793862","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3793862","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"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 Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7144457697868347,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G102097649","display_name":null,"funder_award_id":"No. 62272198, No. 62276277","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1312685195","display_name":null,"funder_award_id":"2024A1515010121","funder_id":"https://openalex.org/F4320337111","funder_display_name":"Basic and Applied Basic Research Foundation of Guangdong Province"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320337111","display_name":"Basic and Applied Basic Research Foundation of Guangdong Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2054141820","https://openalex.org/W2911778742","https://openalex.org/W4408007152"],"related_works":[],"abstract_inverted_index":{"Graph":[0],"Neural":[1],"Networks":[2],"(GNNs)":[3],"have":[4],"demonstrated":[5],"strong":[6],"representation":[7],"learning":[8,17,45,76,102,132],"capabilities":[9],"in":[10,131,198],"recommender":[11],"systems,":[12],"particularly":[13],"under":[14],"the":[15,20,74,104,115],"contrastive":[16,44,75,101],"paradigm,":[18],"where":[19],"construction":[21],"of":[22,120,164],"positive":[23],"and":[24,34,59,70,117,147,172,186],"negative":[25],"sample":[26],"pairs":[27],"effectively":[28,63],"captures":[29],"latent":[30],"relations":[31],"between":[32],"users":[33],"items,":[35],"thereby":[36],"significantly":[37],"enhancing":[38],"recommendation":[39,96,180,200],"performance.":[40,201],"However,":[41],"existing":[42],"graph":[43,90,105,141],"methods":[46],"predominantly":[47],"rely":[48],"on":[49,177],"static":[50],"augmentation":[51],"strategies,":[52],"lacking":[53],"adaptability":[54],"to":[55,112,128,143],"diverse":[56],"user":[57,68],"behaviors":[58],"semantic":[60,118,136],"structures.":[61],"Moreover,":[62],"integrating":[64],"external":[65],"knowledge":[66,187],"(e.g.,":[67],"attributes":[69,188],"item":[71],"semantics)":[72],"into":[73],"process":[77],"remains":[78],"a":[79,89,161],"major":[80],"challenge.":[81],"To":[82],"address":[83],"these":[84],"limitations,":[85],"we":[86],"propose":[87],"ProGraph,":[88],"prompt":[91,106,166],"tuning":[92,159],"framework":[93],"tailored":[94],"for":[95],"tasks.":[97],"ProGraph":[98,156,191],"introduces":[99],"adaptive":[100],"within":[103],"mechanism,":[107],"enhanced":[108],"by":[109],"knowledge-aware":[110],"guidance,":[111],"improve":[113],"both":[114],"discriminability":[116],"generalization":[119],"learned":[121],"representations.":[122],"Specifically,":[123],"it":[124],"employs":[125],"structured":[126],"prompts":[127],"guide":[129],"GNNs":[130],"embeddings":[133],"across":[134],"multiple":[135],"subspaces,":[137],"while":[138],"incorporating":[139],"knowledge-assisted":[140],"views":[142],"preserve":[144],"structural":[145],"consistency":[146],"better":[148,170],"handle":[149],"heterogeneous":[150],"attributes.":[151],"Unlike":[152],"traditional":[153],"full-parameter":[154],"optimization,":[155],"enables":[157],"efficient":[158],"with":[160,182],"small":[162],"number":[163],"learnable":[165],"parameters,":[167],"thus":[168],"achieving":[169],"transferability":[171],"modular":[173],"compatibility.":[174],"Extensive":[175],"experiments":[176],"three":[178],"real-world":[179],"datasets":[181],"rich":[183],"interaction":[184],"records":[185],"demonstrate":[189],"that":[190],"consistently":[192],"outperforms":[193],"several":[194],"representative":[195],"state-of-the-art":[196],"baselines":[197],"top-K":[199]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-02-06T00:00:00"}
