{"id":"https://openalex.org/W4224316953","doi":"https://doi.org/10.1145/3485447.3511929","title":"Exploring Edge Disentanglement for Node Classification","display_name":"Exploring Edge Disentanglement for Node Classification","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4224316953","doi":"https://doi.org/10.1145/3485447.3511929"},"language":"en","primary_location":{"id":"doi:10.1145/3485447.3511929","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3511929","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":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2202.11245","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053042660","display_name":"Tianxiang Zhao","orcid":"https://orcid.org/0000-0003-4504-7809"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianxiang Zhao","raw_affiliation_strings":["The Pennsylvania State University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060725887","display_name":"X. D. Zhang","orcid":"https://orcid.org/0000-0003-0940-6595"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiang Zhang","raw_affiliation_strings":["The Pennsylvania State University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011048500","display_name":"Suhang Wang","orcid":"https://orcid.org/0000-0003-3448-4878"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Suhang Wang","raw_affiliation_strings":["The Pennsylvania State University, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Pennsylvania State University, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":4.7236,"has_fulltext":false,"cited_by_count":29,"citation_normalized_percentile":{"value":0.96035549,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1028","last_page":"1036"},"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9944999814033508,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9786999821662903,"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/computer-science","display_name":"Computer science","score":0.7286937832832336},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.7219545841217041},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6195119619369507},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.554019033908844},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5306711792945862},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5031949877738953},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.46206316351890564},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3918919861316681},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3907119333744049},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.09028548002243042}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7286937832832336},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.7219545841217041},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6195119619369507},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.554019033908844},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5306711792945862},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5031949877738953},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.46206316351890564},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3918919861316681},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3907119333744049},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.09028548002243042},{"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},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3485447.3511929","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3511929","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"},{"id":"pmh:oai:arXiv.org:2202.11245","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2202.11245","pdf_url":"https://arxiv.org/pdf/2202.11245","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2202.11245","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2202.11245","pdf_url":"https://arxiv.org/pdf/2202.11245","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6700000166893005}],"awards":[{"id":"https://openalex.org/G125128811","display_name":null,"funder_award_id":"W911NF-2110198","funder_id":"https://openalex.org/F4320338281","funder_display_name":"Army Research Office"},{"id":"https://openalex.org/G7405368409","display_name":"CAREER: Novel Approaches for Mining Large and Complex Networks","funder_award_id":"1707548","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320338281","display_name":"Army Research Office","ror":"https://ror.org/05epdh915"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W1662382123","https://openalex.org/W2154851992","https://openalex.org/W2465015709","https://openalex.org/W2606780347","https://openalex.org/W2778227677","https://openalex.org/W2907492528","https://openalex.org/W2911286998","https://openalex.org/W2914721378","https://openalex.org/W2931367569","https://openalex.org/W2936503027","https://openalex.org/W2945420892","https://openalex.org/W2962711740","https://openalex.org/W2964015378","https://openalex.org/W2964113829","https://openalex.org/W2981806891","https://openalex.org/W2987232971","https://openalex.org/W2996428491","https://openalex.org/W2998324911","https://openalex.org/W3005552578","https://openalex.org/W3005644236","https://openalex.org/W3023371261","https://openalex.org/W3024183470","https://openalex.org/W3036446966","https://openalex.org/W3036974265","https://openalex.org/W3086452730","https://openalex.org/W3093410149","https://openalex.org/W3093551363","https://openalex.org/W3099152386","https://openalex.org/W3104097132","https://openalex.org/W3105259638","https://openalex.org/W3122063025","https://openalex.org/W3134210100","https://openalex.org/W3134509497","https://openalex.org/W3136543599","https://openalex.org/W3136640655","https://openalex.org/W3166215705","https://openalex.org/W3169350676","https://openalex.org/W3171723757","https://openalex.org/W4210257598","https://openalex.org/W4212890525","https://openalex.org/W4285723986","https://openalex.org/W4286795917","https://openalex.org/W4287754915","https://openalex.org/W4288064365","https://openalex.org/W4288363255","https://openalex.org/W4289699827","https://openalex.org/W4294558607","https://openalex.org/W4303685257"],"related_works":["https://openalex.org/W2280422768","https://openalex.org/W3143197806","https://openalex.org/W4252555497","https://openalex.org/W3121175838","https://openalex.org/W3016293053","https://openalex.org/W1690653314","https://openalex.org/W2401723157","https://openalex.org/W2065055572","https://openalex.org/W2784269775","https://openalex.org/W2952904874"],"abstract_inverted_index":{"Edges":[0],"in":[1,20,31,58,79],"real-world":[2,180],"graphs":[3],"are":[4,39,117,145,158],"typically":[5],"formed":[6],"by":[7],"a":[8,21,67,120],"variety":[9],"of":[10,85,94,141],"factors":[11,38],"and":[12,51,70,101,151,154,174],"carry":[13],"diverse":[14],"relation":[15],"semantics.":[16],"For":[17],"example,":[18],"connections":[19],"social":[22],"network":[23],"could":[24],"indicate":[25],"friendship,":[26],"being":[27],"colleagues,":[28],"or":[29],"living":[30],"the":[32,48,83,109,130,142],"same":[33],"neighborhood.":[34],"However,":[35],"these":[36,62,114],"latent":[37],"usually":[40],"concealed":[41],"behind":[42],"mere":[43],"edge":[44,95,111,122,138],"existence":[45],"due":[46],"to":[47,107,125,135,147,167],"data":[49],"collection":[50],"graph":[52,59],"formation":[53],"processes.":[54],"Despite":[55],"rapid":[56],"developments":[57],"learning":[60],"over":[61],"years,":[63],"most":[64],"models":[65],"take":[66],"holistic":[68],"approach":[69],"treat":[71],"all":[72],"edges":[73,81],"as":[74,160],"equal.":[75],"One":[76],"major":[77],"difficulty":[78],"disentangling":[80],"is":[82,165],"lack":[84],"explicit":[86],"supervisions.":[87],"In":[88],"this":[89],"work,":[90],"with":[91,129,170],"close":[92],"examination":[93],"patterns,":[96],"we":[97,175],"propose":[98],"three":[99,103],"heuristics":[100],"design":[102],"corresponding":[104],"pretext":[105],"tasks":[106,116],"guide":[108],"automatic":[110,137],"disentanglement.":[112,139],"Concretely,":[113],"self-supervision":[115],"enforced":[118],"on":[119,178],"designed":[121],"disentanglement":[123,143],"module":[124,144],"be":[126,168],"trained":[127],"jointly":[128],"downstream":[131],"node":[132,161],"classification":[133],"task":[134],"encourage":[136],"Channels":[140],"expected":[146],"capture":[148],"distinguishable":[149],"relations":[150],"neighborhood":[152],"interactions,":[153],"outputs":[155],"from":[156],"them":[157],"aggregated":[159],"representations.":[162],"The":[163],"proposed":[164],"easy":[166],"incorporated":[169],"various":[171],"neural":[172],"architectures,":[173],"conduct":[176],"experiments":[177],"6":[179],"datasets.":[181],"Empirical":[182],"results":[183],"show":[184],"that":[185],"it":[186],"can":[187],"achieve":[188],"significant":[189],"performance":[190],"gains.":[191]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":2}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}
