{"id":"https://openalex.org/W4321608130","doi":"https://doi.org/10.1109/tmm.2023.3248173","title":"Dual Fusion-Propagation Graph Neural Network for Multi-View Clustering","display_name":"Dual Fusion-Propagation Graph Neural Network for Multi-View Clustering","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4321608130","doi":"https://doi.org/10.1109/tmm.2023.3248173"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2023.3248173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3248173","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Multimedia","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/A5042079993","display_name":"Shunxin Xiao","orcid":"https://orcid.org/0000-0003-1187-8719"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shunxin Xiao","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091188575","display_name":"Shide Du","orcid":"https://orcid.org/0000-0002-6354-4705"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shide Du","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084849129","display_name":"Zhaoliang Chen","orcid":"https://orcid.org/0000-0002-7832-908X"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaoliang Chen","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100755782","display_name":"Yunhe Zhang","orcid":"https://orcid.org/0000-0002-8080-3828"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhe Zhang","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100604225","display_name":"Shiping Wang","orcid":"https://orcid.org/0000-0001-5195-9682"},"institutions":[{"id":"https://openalex.org/I80947539","display_name":"Fuzhou University","ror":"https://ror.org/011xvna82","country_code":"CN","type":"education","lineage":["https://openalex.org/I80947539"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiping Wang","raw_affiliation_strings":["College of Computer and Data Science, Fuzhou University, Fuzhou, China"],"affiliations":[{"raw_affiliation_string":"College of Computer and Data Science, Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5042079993"],"corresponding_institution_ids":["https://openalex.org/I80947539"],"apc_list":null,"apc_paid":null,"fwci":10.09,"has_fulltext":false,"cited_by_count":58,"citation_normalized_percentile":{"value":0.98678506,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"25","issue":null,"first_page":"9203","last_page":"9215"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9993000030517578,"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"}},"topics":[{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9993000030517578,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9818000197410583,"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/T13731","display_name":"Advanced Computing and Algorithms","score":0.9761999845504761,"subfield":{"id":"https://openalex.org/subfields/3322","display_name":"Urban Studies"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8180257678031921},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5599567890167236},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5463084578514099},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5034665465354919},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.497604638338089},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4279310405254364},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.42715051770210266},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4167936444282532},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4122505187988281},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4105665683746338},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.398957222700119},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35656875371932983}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8180257678031921},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5599567890167236},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5463084578514099},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5034665465354919},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.497604638338089},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4279310405254364},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.42715051770210266},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4167936444282532},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4122505187988281},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4105665683746338},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.398957222700119},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35656875371932983},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2023.3248173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2023.3248173","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2979006455","display_name":null,"funder_award_id":"62276065","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3794798619","display_name":null,"funder_award_id":"U21A20472","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":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W201974436","https://openalex.org/W1907775068","https://openalex.org/W2605146283","https://openalex.org/W2740464254","https://openalex.org/W2741998188","https://openalex.org/W2756626360","https://openalex.org/W2809299793","https://openalex.org/W2891953767","https://openalex.org/W2896169497","https://openalex.org/W2899604627","https://openalex.org/W2906217954","https://openalex.org/W2921065608","https://openalex.org/W2945591540","https://openalex.org/W2950212750","https://openalex.org/W2951652447","https://openalex.org/W2962947748","https://openalex.org/W2963764569","https://openalex.org/W2964051675","https://openalex.org/W2964251001","https://openalex.org/W2964732194","https://openalex.org/W2965624713","https://openalex.org/W2965744772","https://openalex.org/W2988869004","https://openalex.org/W2996771119","https://openalex.org/W2997573100","https://openalex.org/W2997739739","https://openalex.org/W2998662521","https://openalex.org/W3005916310","https://openalex.org/W3007910141","https://openalex.org/W3008273026","https://openalex.org/W3008681464","https://openalex.org/W3012918605","https://openalex.org/W3034277777","https://openalex.org/W3034903580","https://openalex.org/W3035397262","https://openalex.org/W3035663159","https://openalex.org/W3044063956","https://openalex.org/W3102794373","https://openalex.org/W3160988939","https://openalex.org/W3195106575","https://openalex.org/W3208506679","https://openalex.org/W4214876032","https://openalex.org/W4220873374","https://openalex.org/W4220942341","https://openalex.org/W4290713716","https://openalex.org/W4293249645","https://openalex.org/W6631216910","https://openalex.org/W6678914141","https://openalex.org/W6726873649","https://openalex.org/W6731811539","https://openalex.org/W6749180256","https://openalex.org/W6752110883","https://openalex.org/W6762833281","https://openalex.org/W6770064641","https://openalex.org/W6779032261"],"related_works":["https://openalex.org/W2165912799","https://openalex.org/W2735662278","https://openalex.org/W2382615723","https://openalex.org/W4311804456","https://openalex.org/W1987484445","https://openalex.org/W2623658258","https://openalex.org/W2143413548","https://openalex.org/W1969219540","https://openalex.org/W2370459448","https://openalex.org/W2105067402"],"abstract_inverted_index":{"Deep":[0],"multi-view":[1,37,89,129],"representation":[2,10],"learning":[3],"focuses":[4],"on":[5,144],"training":[6],"a":[7,52],"unified":[8],"low-dimensional":[9],"for":[11],"data":[12],"with":[13,97,132,154],"multiple":[14,57,121],"sources":[15],"or":[16,65],"modalities.":[17],"With":[18],"the":[19,61,69,102,115,133,138],"rapidly":[20],"growing":[21],"attention":[22],"of":[23,63,135],"graph":[24,34],"neural":[25],"networks,":[26],"more":[27,29],"and":[28,55,84,100,109,117,137],"researchers":[30],"have":[31,42],"introduced":[32],"various":[33],"models":[35],"into":[36],"learning.":[38],"Although":[39],"considerable":[40],"achievements":[41],"been":[43],"made,":[44],"most":[45],"existing":[46],"methods":[47],"usually":[48],"propagate":[49],"information":[50,58,119,130],"in":[51],"single":[53],"view":[54],"fuse":[56],"only":[59],"from":[60],"perspective":[62],"attributes":[64,134],"relationships.":[66],"To":[67],"solve":[68],"aforementioned":[70],"problems,":[71],"we":[72],"propose":[73],"an":[74],"efficient":[75],"model":[76],"termed":[77],"Dual":[78],"Fusion-Propagation":[79],"Graph":[80],"Neural":[81],"Network":[82],"(DFP-GNN)":[83],"apply":[85],"it":[86],"to":[87],"deep":[88],"clustering":[90],"tasks.":[91],"The":[92,106,124],"proposed":[93,107],"method":[94],"is":[95],"designed":[96,125],"three":[98],"submodules":[99],"has":[101],"following":[103],"merits:":[104],"a)":[105],"view-specific":[108],"cross-view":[110],"propagation":[111],"modules":[112],"can":[113],"capture":[114],"consistency":[116],"complementarity":[118],"among":[120,140],"views;":[122],"b)":[123],"fusion":[126,131],"module":[127],"performs":[128],"nodes":[136],"relationships":[139],"them":[141],"simultaneously.":[142],"Experiments":[143],"popular":[145],"databases":[146],"show":[147],"that":[148],"DFP-GNN":[149],"achieves":[150],"significant":[151],"results":[152],"compared":[153],"several":[155],"state-of-the-art":[156],"algorithms.":[157]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":25},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":12}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
