{"id":"https://openalex.org/W2966720510","doi":"https://doi.org/10.24963/ijcai.2019/366","title":"Dynamic Hypergraph Neural Networks","display_name":"Dynamic Hypergraph Neural Networks","publication_year":2019,"publication_date":"2019-07-28","ids":{"openalex":"https://openalex.org/W2966720510","doi":"https://doi.org/10.24963/ijcai.2019/366","mag":"2966720510"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2019/366","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/366","pdf_url":"https://www.ijcai.org/proceedings/2019/0366.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.ijcai.org/proceedings/2019/0366.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103086589","display_name":"Jianwen Jiang","orcid":"https://orcid.org/0000-0002-8449-6992"},"institutions":[{"id":"https://openalex.org/I29955533","display_name":"Center for Information Technology","ror":"https://ror.org/03jh5a977","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I29955533"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jianwen Jiang","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology(BNRist)","KLISS, School of Software, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology(BNRist)","institution_ids":["https://openalex.org/I29955533"]},{"raw_affiliation_string":"KLISS, School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051515603","display_name":"Yuxuan Wei","orcid":"https://orcid.org/0009-0002-9466-3077"},"institutions":[{"id":"https://openalex.org/I29955533","display_name":"Center for Information Technology","ror":"https://ror.org/03jh5a977","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I29955533"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Yuxuan Wei","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology(BNRist)","KLISS, School of Software, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology(BNRist)","institution_ids":["https://openalex.org/I29955533"]},{"raw_affiliation_string":"KLISS, School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101819284","display_name":"Yifan Feng","orcid":"https://orcid.org/0000-0003-0878-2986"},"institutions":[{"id":"https://openalex.org/I191208505","display_name":"Xiamen University","ror":"https://ror.org/00mcjh785","country_code":"CN","type":"education","lineage":["https://openalex.org/I191208505"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Feng","raw_affiliation_strings":["School of Information Science and Engineering, Xiamen University, Xiamen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Xiamen University, Xiamen, China","institution_ids":["https://openalex.org/I191208505"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014932384","display_name":"Jingxuan Cao","orcid":"https://orcid.org/0009-0002-5579-6344"},"institutions":[{"id":"https://openalex.org/I29955533","display_name":"Center for Information Technology","ror":"https://ror.org/03jh5a977","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I29955533"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Jingxuan Cao","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology(BNRist)","KLISS, School of Software, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology(BNRist)","institution_ids":["https://openalex.org/I29955533"]},{"raw_affiliation_string":"KLISS, School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100602494","display_name":"Yue Gao","orcid":"https://orcid.org/0000-0002-4971-590X"},"institutions":[{"id":"https://openalex.org/I29955533","display_name":"Center for Information Technology","ror":"https://ror.org/03jh5a977","country_code":"US","type":"facility","lineage":["https://openalex.org/I1299022934","https://openalex.org/I1299303238","https://openalex.org/I29955533"]},{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Yue Gao","raw_affiliation_strings":["Beijing National Research Center for Information Science and Technology(BNRist)","KLISS, School of Software, Tsinghua University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing National Research Center for Information Science and Technology(BNRist)","institution_ids":["https://openalex.org/I29955533"]},{"raw_affiliation_string":"KLISS, School of Software, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":363,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2635","last_page":"2641"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9997000098228455,"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":0.9997000098228455,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12292","display_name":"Graph Theory and Algorithms","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/hypergraph","display_name":"Hypergraph","score":0.9701119065284729},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7020927667617798},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6486706733703613},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5130914449691772},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5021710395812988},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.49151191115379333},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.4643820524215698},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.42927655577659607},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.380791574716568},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3574906587600708},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3435557186603546},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2272530496120453},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.14313143491744995}],"concepts":[{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.9701119065284729},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7020927667617798},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6486706733703613},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5130914449691772},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5021710395812988},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.49151191115379333},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.4643820524215698},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.42927655577659607},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.380791574716568},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3574906587600708},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3435557186603546},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2272530496120453},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.14313143491744995},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2019/366","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/366","pdf_url":"https://www.ijcai.org/proceedings/2019/0366.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.24963/ijcai.2019/366","is_oa":true,"landing_page_url":"https://doi.org/10.24963/ijcai.2019/366","pdf_url":"https://www.ijcai.org/proceedings/2019/0366.pdf","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2966720510.pdf","grobid_xml":"https://content.openalex.org/works/W2966720510.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1509250914","https://openalex.org/W1982498087","https://openalex.org/W1989889610","https://openalex.org/W2068078373","https://openalex.org/W2075456404","https://openalex.org/W2126792281","https://openalex.org/W2128700566","https://openalex.org/W2153959628","https://openalex.org/W2154851992","https://openalex.org/W2163605009","https://openalex.org/W2170057991","https://openalex.org/W2558460151","https://openalex.org/W2624431344","https://openalex.org/W2807746743","https://openalex.org/W2888975113","https://openalex.org/W2892880750","https://openalex.org/W2963312446","https://openalex.org/W2964015378","https://openalex.org/W2964321699","https://openalex.org/W2979750740","https://openalex.org/W3104097132","https://openalex.org/W4294558607","https://openalex.org/W4297733535","https://openalex.org/W4299395716"],"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/W2472555608","https://openalex.org/W4376608938","https://openalex.org/W4288275998","https://openalex.org/W4214498971"],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"graph/hypergraph-based":[3],"deep":[4,14],"learning":[5,15],"methods":[6,16],"have":[7,129],"attracted":[8],"much":[9],"attention":[10],"from":[11],"researchers.":[12],"These":[13],"take":[17],"graph/hypergraph":[18],"structure":[19,88],"as":[20],"prior":[21],"knowledge":[22],"in":[23,35,102],"the":[24,36,56,82,136,154],"model.":[25],"However,":[26],"hidden":[27],"and":[28,66,114,125,140,156],"important":[29],"relations":[30,101],"are":[31,118,150],"not":[32,76],"directly":[33],"represented":[34],"inherent":[37],"structure.":[38,105],"To":[39],"tackle":[40],"this":[41],"issue,":[42],"we":[43],"propose":[44],"a":[45,77,103],"dynamic":[46,62],"hypergraph":[47,63,73,87,93,104],"neural":[48],"networks":[49],"framework":[50],"(DHGNN),":[51],"which":[52,117],"is":[53,74,95],"composed":[54],"of":[55,59,158],"stacked":[57],"layers":[58],"two":[60,110],"modules:":[61],"construction":[64],"(DHG)":[65],"hypergrpah":[67],"convolution":[68,94,113],"(HGC).":[69],"Considering":[70],"initially":[71],"constructed":[72],"probably":[75],"suitable":[78],"representation":[79],"for":[80],"data,":[81],"DHG":[83],"module":[84,108],"dynamically":[85],"updates":[86],"on":[89,133],"each":[90],"layer.":[91],"Then":[92],"introduced":[96],"to":[97,120,152,161],"encode":[98],"high-order":[99],"data":[100,163],"The":[106],"HGC":[107],"includes":[109],"phases:":[111],"vertex":[112],"hyperedge":[115],"convolution,":[116],"designed":[119],"aggregate":[121],"feature":[122],"among":[123],"vertices":[124],"hyperedges,":[126],"respectively.":[127],"We":[128],"evaluated":[130],"our":[131,159],"method":[132,144,160],"standard":[134],"datasets,":[135],"Cora":[137],"citation":[138],"network":[139],"Microblog":[141],"dataset.":[142],"Our":[143],"outperforms":[145],"state-of-the-art":[146],"methods.":[147],"More":[148],"experiments":[149],"conducted":[151],"demonstrate":[153],"effectiveness":[155],"robustness":[157],"diverse":[162],"distributions.":[164]},"counts_by_year":[{"year":2026,"cited_by_count":19},{"year":2025,"cited_by_count":68},{"year":2024,"cited_by_count":61},{"year":2023,"cited_by_count":63},{"year":2022,"cited_by_count":55},{"year":2021,"cited_by_count":70},{"year":2020,"cited_by_count":24},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
