{"id":"https://openalex.org/W4224317914","doi":"https://doi.org/10.1145/3485447.3512161","title":"Graph Neural Network for Higher-Order Dependency Networks","display_name":"Graph Neural Network for Higher-Order Dependency Networks","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4224317914","doi":"https://doi.org/10.1145/3485447.3512161"},"language":"en","primary_location":{"id":"doi:10.1145/3485447.3512161","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512161","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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 ACM Web Conference 2022","raw_type":"proceedings-article"},"type":"conference-paper","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/A5012455357","display_name":"Di Jin","orcid":"https://orcid.org/0000-0002-7445-9936"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Di Jin","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102447143","display_name":"Yingli Gong","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingli Gong","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100404747","display_name":"Zhi-Qiang Wang","orcid":"https://orcid.org/0000-0003-1326-661X"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiqiang Wang","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065948939","display_name":"Zhizhi Yu","orcid":"https://orcid.org/0000-0001-5954-3593"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhizhi Yu","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009013876","display_name":"Dongxiao He","orcid":"https://orcid.org/0000-0002-1915-4179"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongxiao He","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103195106","display_name":"Yuxiao Huang","orcid":"https://orcid.org/0000-0001-9394-805X"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]},{"id":"https://openalex.org/I4210158842","display_name":"GW Medical Faculty Associates","ror":"https://ror.org/02bn3v102","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I4210158842"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuxiao Huang","raw_affiliation_strings":["Columbian College of Arts and Sciences, George Washington University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbian College of Arts and Sciences, George Washington University, USA","institution_ids":["https://openalex.org/I193531525","https://openalex.org/I4210158842"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100393041","display_name":"Wenjun Wang","orcid":"https://orcid.org/0000-0003-1174-7241"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenjun Wang","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, China","institution_ids":["https://openalex.org/I162868743"]}]}],"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":11,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1622","last_page":"1630"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":1.0,"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":1.0,"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":0.9980000257492065,"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"}},{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9736999869346619,"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/computer-science","display_name":"Computer science","score":0.7896022796630859},{"id":"https://openalex.org/keywords/dependency","display_name":"Dependency (UML)","score":0.6762343645095825},{"id":"https://openalex.org/keywords/dependency-graph","display_name":"Dependency graph","score":0.6620604991912842},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5310141444206238},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.46546295285224915},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.4516158103942871},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37190330028533936},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2665843367576599}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7896022796630859},{"id":"https://openalex.org/C19768560","wikidata":"https://www.wikidata.org/wiki/Q320727","display_name":"Dependency (UML)","level":2,"score":0.6762343645095825},{"id":"https://openalex.org/C16311509","wikidata":"https://www.wikidata.org/wiki/Q4148050","display_name":"Dependency graph","level":3,"score":0.6620604991912842},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5310141444206238},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.46546295285224915},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4516158103942871},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37190330028533936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2665843367576599},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3485447.3512161","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512161","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"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 ACM Web Conference 2022","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4892546666","display_name":null,"funder_award_id":"61876128, 61772361","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":20,"referenced_works":["https://openalex.org/W1888005072","https://openalex.org/W2154851992","https://openalex.org/W2240347590","https://openalex.org/W2393319904","https://openalex.org/W2765811365","https://openalex.org/W2962756421","https://openalex.org/W2963169753","https://openalex.org/W2963224980","https://openalex.org/W2997035976","https://openalex.org/W3036446966","https://openalex.org/W3042770487","https://openalex.org/W3090732917","https://openalex.org/W3099152386","https://openalex.org/W3099375322","https://openalex.org/W3104097132","https://openalex.org/W3152893301","https://openalex.org/W3154818219","https://openalex.org/W3155886566","https://openalex.org/W3168735469","https://openalex.org/W3194841521"],"related_works":["https://openalex.org/W2327631927","https://openalex.org/W2093568763","https://openalex.org/W1985166372","https://openalex.org/W2003096546","https://openalex.org/W2430210575","https://openalex.org/W4289354592","https://openalex.org/W2165069859","https://openalex.org/W2099112646","https://openalex.org/W2626477053","https://openalex.org/W2342550845"],"abstract_inverted_index":{"Graph":[0],"neural":[1],"network":[2,151,169],"(GNN)":[3],"has":[4],"become":[5],"a":[6,175],"popular":[7],"tool":[8],"to":[9,167,214],"analyze":[10],"the":[11,28,38,46,49,56,92,110,125,129,137,144,150,187,190,196,201,208,215,222,227,234,256],"graph":[12,209],"data.":[13],"Existing":[14],"GNNs":[15,80,166],"only":[16,54],"focus":[17],"on":[18,55,61,237],"networks":[19,26,33,100,184,240],"with":[20,152,182,241,246],"first-order":[21,159,216],"dependency,":[22,40,243],"that":[23],"is,":[24],"conventional":[25,158],"following":[27],"Markov":[29],"property.":[30],"However,":[31],"many":[32],"in":[34,101,143,186,212],"real":[35,239],"life":[36],"own":[37],"higher-order":[39,99,122,145,153,183,191,228,242,261],"such":[41],"as":[42,120,155,195],"click-stream":[43],"data":[44,68],"where":[45],"choice":[47],"of":[48,66,117,132,136,255],"next":[50],"page":[51,58],"depends":[52],"not":[53],"current":[57,111,138],"but":[59],"also":[60,220],"previous":[62],"pages.":[63],"This":[64],"kind":[65],"sequential":[67],"from":[69,226],"complex":[70],"systems":[71],"(including":[72],"natural":[73],"dependencies)":[74],"are":[75],"often":[76],"ignored":[77],"by":[78,109],"existing":[79],"which":[81,259],"makes":[82],"them":[83],"ineffective.":[84],"To":[85],"address":[86],"this":[87,102],"problem,":[88],"we":[89,105,140,172,219],"propose":[90,174],"for":[91,98,180],"first":[93],"time":[94],"new":[95,176,235,257],"GNN":[96,178],"approaches":[97,236,258],"paper.":[103],"First,":[104],"form":[106],"sequence":[107],"fragments":[108],"node":[112,202,224],"and":[113,161,205,244],"its":[114],"predecessor":[115],"nodes":[116,135],"different":[118,133],"orders":[119],"candidate":[121],"dependencies.":[123],"When":[124],"fragment":[126],"significantly":[127],"affects":[128],"probability":[130],"distribution":[131],"successor":[134],"node,":[139],"include":[141],"it":[142,164],"dependency":[146,154,192,229],"set.":[147],"We":[148,231],"formulize":[149],"an":[156],"augmented":[157],"network,":[160],"then":[162],"feed":[163],"into":[165],"derive":[168],"embeddings.":[170],"Moreover,":[171],"further":[173],"end-to-end":[177],"framework":[179],"dealing":[181],"directly":[185],"model.":[188],"Specifically,":[189],"is":[193,203],"used":[194],"neighbor":[197,217],"aggregation":[198],"controller":[199],"when":[200],"embedded":[204],"updated.":[206],"In":[207],"convolutional":[210],"layer,":[211],"addition":[213],"information,":[218],"aggregate":[221],"middle":[223],"information":[225],"segment.":[230],"finally":[232],"test":[233],"three":[238],"compare":[245],"some":[247],"state-of-the-art":[248],"methods.":[249],"The":[250],"results":[251],"show":[252],"significant":[253],"improvements":[254],"consider":[260],"dependency.":[262]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
