{"id":"https://openalex.org/W4403791348","doi":"https://doi.org/10.1145/3664647.3681585","title":"Enhancing Multi-view Graph Neural Network with Cross-view Confluent Message Passing","display_name":"Enhancing Multi-view Graph Neural Network with Cross-view Confluent Message Passing","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403791348","doi":"https://doi.org/10.1145/3664647.3681585"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3681585","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681585","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-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/A5045720576","display_name":"Shuman Zhuang","orcid":"https://orcid.org/0009-0007-1106-1764"},"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":"Shuman Zhuang","raw_affiliation_strings":["Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0009-0007-1106-1764","affiliations":[{"raw_affiliation_string":"Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5032715565","display_name":"Sujia Huang","orcid":"https://orcid.org/0000-0002-4745-2157"},"institutions":[{"id":"https://openalex.org/I36399199","display_name":"Nanjing University of Science and Technology","ror":"https://ror.org/00xp9wg62","country_code":"CN","type":"education","lineage":["https://openalex.org/I36399199"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Sujia Huang","raw_affiliation_strings":["Nanjing University of Science and Technology, Nanjing, China"],"raw_orcid":"https://orcid.org/0000-0002-4745-2157","affiliations":[{"raw_affiliation_string":"Nanjing University of Science and Technology, Nanjing, China","institution_ids":["https://openalex.org/I36399199"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Wei Huang","orcid":"https://orcid.org/0000-0002-2910-3447"},"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":"Wei Huang","raw_affiliation_strings":["Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-2910-3447","affiliations":[{"raw_affiliation_string":"Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100457620","display_name":"Yuhong Chen","orcid":"https://orcid.org/0009-0000-9073-7038"},"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":"Yuhong Chen","raw_affiliation_strings":["Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0009-0000-9073-7038","affiliations":[{"raw_affiliation_string":"Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023510892","display_name":"Zhihao Wu","orcid":"https://orcid.org/0000-0001-5835-9903"},"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":"Zhihao Wu","raw_affiliation_strings":["Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0001-5835-9903","affiliations":[{"raw_affiliation_string":"Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058120371","display_name":"Ximeng Liu","orcid":"https://orcid.org/0000-0002-4238-3295"},"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":"Ximeng Liu","raw_affiliation_strings":["Fuzhou University, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-4238-3295","affiliations":[{"raw_affiliation_string":"Fuzhou University, Fuzhou, China","institution_ids":["https://openalex.org/I80947539"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5045720576"],"corresponding_institution_ids":["https://openalex.org/I80947539"],"apc_list":null,"apc_paid":null,"fwci":1.3171,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.84232938,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"10065","last_page":"10074"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9905999898910522,"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"}},{"id":"https://openalex.org/T12702","display_name":"Brain Tumor Detection and Classification","score":0.9883000254631042,"subfield":{"id":"https://openalex.org/subfields/2808","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7629846334457397},{"id":"https://openalex.org/keywords/message-passing","display_name":"Message passing","score":0.6264917850494385},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.45051804184913635},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43810051679611206},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.328069269657135},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.32733941078186035},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21846023201942444},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.20864006876945496}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7629846334457397},{"id":"https://openalex.org/C854659","wikidata":"https://www.wikidata.org/wiki/Q1859284","display_name":"Message passing","level":2,"score":0.6264917850494385},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.45051804184913635},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43810051679611206},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.328069269657135},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.32733941078186035},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21846023201942444},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.20864006876945496}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3681585","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681585","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W1937059634","https://openalex.org/W2016384870","https://openalex.org/W2050551672","https://openalex.org/W2672266311","https://openalex.org/W2894142921","https://openalex.org/W2911286998","https://openalex.org/W2964051675","https://openalex.org/W2997686727","https://openalex.org/W2998358581","https://openalex.org/W2998662521","https://openalex.org/W3009901425","https://openalex.org/W3011257201","https://openalex.org/W3035739162","https://openalex.org/W3068123808","https://openalex.org/W3095746859","https://openalex.org/W3099064659","https://openalex.org/W3103557031","https://openalex.org/W3128443161","https://openalex.org/W3152560880","https://openalex.org/W3160988939","https://openalex.org/W3177385106","https://openalex.org/W3191867763","https://openalex.org/W3194856818","https://openalex.org/W4210257598","https://openalex.org/W4226102968","https://openalex.org/W4283789226","https://openalex.org/W4283817628","https://openalex.org/W4290943973","https://openalex.org/W4290948206","https://openalex.org/W4306705227","https://openalex.org/W4312459443","https://openalex.org/W4321113904","https://openalex.org/W4360753265","https://openalex.org/W4360770799","https://openalex.org/W4382237410","https://openalex.org/W4382239875","https://openalex.org/W4386075537","https://openalex.org/W4386083068","https://openalex.org/W4386648881","https://openalex.org/W4387967896","https://openalex.org/W4387968004","https://openalex.org/W4387968084","https://openalex.org/W4387968167","https://openalex.org/W4390317709","https://openalex.org/W4390970440","https://openalex.org/W4392244941","https://openalex.org/W4392543743","https://openalex.org/W4393153051","https://openalex.org/W4393159534","https://openalex.org/W6640561700","https://openalex.org/W6807384801","https://openalex.org/W6846424470"],"related_works":["https://openalex.org/W2978729728","https://openalex.org/W4288966080","https://openalex.org/W2510374584","https://openalex.org/W2134852660","https://openalex.org/W1530347314","https://openalex.org/W2901069556","https://openalex.org/W1556686321","https://openalex.org/W1902983110","https://openalex.org/W2390507337","https://openalex.org/W4389325792"],"abstract_inverted_index":{"With":[0],"the":[1,18,42,62,67,71,83,93,102,131,146],"growing":[2],"diversity":[3],"of":[4,70,133,158,170],"data":[5,20,171,174],"sources,":[6],"multi-view":[7,19,22,24,35,57,75,98,127,136],"learning":[8,36],"methods":[9],"have":[10,29],"attracted":[11],"considerable":[12],"attention.":[13],"Among":[14],"these,":[15],"by":[16,130],"modeling":[17],"as":[21],"graphs,":[23],"Graph":[25,115],"Neural":[26,116],"Networks":[27,117],"(GNNs)":[28],"shown":[30],"encouraging":[31],"performance":[32],"on":[33,61,74,167],"various":[34],"tasks.":[37],"The":[38,185],"message":[39,72,84,99],"passing":[40,73,85],"is":[41,187],"critical":[43],"mechanism":[44,86],"empowering":[45],"GNNs":[46,58],"with":[47,119],"superior":[48,181],"capacity":[49],"to":[50,95],"process":[51],"complex":[52],"graph":[53,149],"data.":[54],"However,":[55],"most":[56],"are":[59],"designed":[60],"well-established":[63],"overall":[64],"framework,":[65],"overlooking":[66],"intrinsic":[68],"challenges":[69],"scenarios.":[76],"To":[77],"clarify":[78],"this,":[79],"we":[80,107],"first":[81],"revisit":[82],"from":[87],"a":[88,97],"Laplacian":[89,137],"smoothing":[90,138],"perspective,":[91],"revealing":[92],"key":[94],"designing":[96],"passing.":[100],"Following":[101],"analysis,":[103],"in":[104],"this":[105],"paper,":[106],"propose":[108],"an":[109,134],"enhanced":[110],"GNN":[111],"framework":[112],"termed":[113],"<u>C</u>onfluent":[114],"(CGNN),":[118],"<u>C</u>ross-view":[120],"<u>C</u>onfulent":[121],"<u>M</u>essage":[122],"<u>P</u>ssing":[123],"(CCMP)":[124],"tailored":[125],"for":[126],"learning.":[128],"Inspired":[129],"optimization":[132],"improved":[135],"problem,":[139],"CCMP":[140],"contains":[141],"three":[142],"sub-modules":[143],"that":[144,176],"enable":[145],"interaction":[147],"between":[148],"structures":[150],"and":[151,160,183],"consistent":[152],"representations,":[153],"which":[154],"makes":[155],"it":[156],"aware":[157],"consistency":[159],"complementarity":[161],"information":[162],"across":[163],"views.":[164],"Extensive":[165],"experiments":[166],"four":[168],"types":[169],"including":[172],"multi-modality":[173],"demonstrate":[175],"our":[177],"proposed":[178],"model":[179],"exhibits":[180],"effectiveness":[182],"robustness.":[184],"code":[186],"available":[188],"at":[189],"https://github.com/shumanzhuang/CGNN.":[190]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-28T14:05:53.105641","created_date":"2025-10-10T00:00:00"}