{"id":"https://openalex.org/W3121835124","doi":"https://doi.org/10.1145/3442381.3449834","title":"Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs","display_name":"Knowledge-Preserving Incremental Social Event Detection via Heterogeneous GNNs","publication_year":2021,"publication_date":"2021-04-19","ids":{"openalex":"https://openalex.org/W3121835124","doi":"https://doi.org/10.1145/3442381.3449834","mag":"3121835124"},"language":"en","primary_location":{"id":"doi:10.1145/3442381.3449834","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449834","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3442381.3449834","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102734597","display_name":"Yuwei Cao","orcid":"https://orcid.org/0000-0001-6579-3441"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yuwei Cao","raw_affiliation_strings":["University of Illinois at Chicago, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100740618","display_name":"Hao Peng","orcid":"https://orcid.org/0000-0001-7422-630X"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Peng","raw_affiliation_strings":["Beihang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007475662","display_name":"Jia Wu","orcid":"https://orcid.org/0000-0002-1371-5801"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jia Wu","raw_affiliation_strings":["Macquarie University, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macquarie University, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052902632","display_name":"Yingtong Dou","orcid":"https://orcid.org/0000-0003-0470-6716"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yingtong Dou","raw_affiliation_strings":["University of Illinois at Chicago, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, USA","institution_ids":["https://openalex.org/I39422238"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100380463","display_name":"Jianxin Li","orcid":"https://orcid.org/0000-0001-5152-0055"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianxin Li","raw_affiliation_strings":["Beihang University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beihang University, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5036357902","display_name":"Philip S. Yu","orcid":"https://orcid.org/0000-0002-3491-5968"},"institutions":[{"id":"https://openalex.org/I39422238","display_name":"University of Illinois Chicago","ror":"https://ror.org/02mpq6x41","country_code":"US","type":"education","lineage":["https://openalex.org/I39422238"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip S. Yu","raw_affiliation_strings":["University of Illinois at Chicago, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Illinois at Chicago, USA","institution_ids":["https://openalex.org/I39422238"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":96,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3383","last_page":"3395"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9998000264167786,"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/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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9922999739646912,"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":0.7946057319641113},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5354172587394714},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4957343339920044},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4920608401298523},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.47170042991638184},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4520376920700073},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.42901208996772766},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.32428011298179626}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7946057319641113},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5354172587394714},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4957343339920044},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4920608401298523},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47170042991638184},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4520376920700073},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.42901208996772766},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.32428011298179626},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3442381.3449834","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449834","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2101.08747","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2101.08747","pdf_url":"https://arxiv.org/pdf/2101.08747","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"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":"doi:10.1145/3442381.3449834","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3442381.3449834","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Web Conference 2021","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":63,"referenced_works":["https://openalex.org/W658020064","https://openalex.org/W1614298861","https://openalex.org/W1673310716","https://openalex.org/W1880262756","https://openalex.org/W1966193717","https://openalex.org/W1983719983","https://openalex.org/W2079735306","https://openalex.org/W2096733369","https://openalex.org/W2109865831","https://openalex.org/W2110676972","https://openalex.org/W2135674549","https://openalex.org/W2156483112","https://openalex.org/W2160654919","https://openalex.org/W2162833336","https://openalex.org/W2250539671","https://openalex.org/W2404243041","https://openalex.org/W2519887557","https://openalex.org/W2523246573","https://openalex.org/W2589855959","https://openalex.org/W2598634450","https://openalex.org/W2609002182","https://openalex.org/W2612759981","https://openalex.org/W2613214602","https://openalex.org/W2624431344","https://openalex.org/W2741643124","https://openalex.org/W2763244488","https://openalex.org/W2766437698","https://openalex.org/W2786446225","https://openalex.org/W2887997457","https://openalex.org/W2896457183","https://openalex.org/W2911286998","https://openalex.org/W2914963716","https://openalex.org/W2945876331","https://openalex.org/W2950369002","https://openalex.org/W2962756421","https://openalex.org/W2962767366","https://openalex.org/W2963403868","https://openalex.org/W2963782635","https://openalex.org/W2963840760","https://openalex.org/W2963858333","https://openalex.org/W2963919031","https://openalex.org/W2964015378","https://openalex.org/W2964189064","https://openalex.org/W2965857891","https://openalex.org/W2966779056","https://openalex.org/W2970066309","https://openalex.org/W3010206893","https://openalex.org/W3012871709","https://openalex.org/W3013642887","https://openalex.org/W3014137702","https://openalex.org/W3023480082","https://openalex.org/W3027864066","https://openalex.org/W3098230111","https://openalex.org/W3099206234","https://openalex.org/W3106098584","https://openalex.org/W3114303065","https://openalex.org/W3189092450","https://openalex.org/W4231510805","https://openalex.org/W4285719527","https://openalex.org/W4294558607","https://openalex.org/W4297571622","https://openalex.org/W4297733535","https://openalex.org/W4385245566"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W2965083567","https://openalex.org/W4235240664","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2889616422","https://openalex.org/W2089704382","https://openalex.org/W1983399550","https://openalex.org/W97075385","https://openalex.org/W2357523926"],"abstract_inverted_index":{"Social":[0],"events":[1,172],"provide":[2],"valuable":[3],"insights":[4],"into":[5,121],"group":[6],"social":[7,32,39,84,109,119,123,185],"behaviors":[8],"and":[9,12,23,28,50,65,79,129,173,197,213],"public":[10],"concerns":[11],"therefore":[13],"have":[14],"many":[15],"applications":[16],"in":[17,42,83],"fields":[18],"such":[19],"as":[20,73],"product":[21],"recommendation":[22],"crisis":[24],"management.":[25],"The":[26],"complexity":[27],"streaming":[29],"nature":[30],"of":[31,71,134,157,167,225],"messages":[33,120],"make":[34],"it":[35],"appealing":[36],"to":[37,125,142,169,202,217],"address":[38],"event":[40,110,158],"detection":[41],"an":[43],"incremental":[44,63,108],"learning":[45,165],"setting,":[46],"where":[47],"acquiring,":[48],"preserving,":[49],"extending":[51],"knowledge":[52,72,137,176],"are":[53],"major":[54],"concerns.":[55],"Most":[56],"existing":[57],"methods,":[58],"including":[59],"those":[60],"based":[61],"on":[62],"clustering":[64],"community":[66],"detection,":[67],"learn":[68],"limited":[69],"amounts":[70],"they":[74,87],"ignore":[75],"the":[76,131,143,163,223],"rich":[77],"semantics":[78],"structural":[80],"information":[81],"contained":[82],"data.":[85,180],"Moreover,":[86],"cannot":[88],"memorize":[89],"previously":[90,178],"acquired":[91],"knowledge.":[92],"In":[93],"this":[94],"paper,":[95],"we":[96],"propose":[97],"a":[98,154,189,204],"novel":[99],"Knowledge-Preserving":[100],"Incremental":[101],"Heterogeneous":[102],"Graph":[103],"Neural":[104],"Network":[105],"(KPGNN)":[106],"for":[107,136,194],"detection.":[111],"To":[112,139,181],"acquire":[113],"more":[114],"knowledge,":[115],"KPGNN":[116,146,187,208,226],"models":[117],"complex":[118],"unified":[122],"graphs":[124],"facilitate":[126],"data":[127,201],"utilization":[128],"explores":[130],"expressive":[132],"power":[133],"GNNs":[135,168],"extraction.":[138],"continuously":[140],"adapt":[141],"incoming":[144],"data,":[145],"adopts":[147,188],"contrastive":[148],"loss":[149],"terms":[150],"that":[151],"cope":[152],"with":[153,183],"changing":[155],"number":[156],"classes.":[159],"It":[160],"also":[161],"leverages":[162],"inductive":[164],"ability":[166],"efficiently":[170],"detect":[171],"extends":[174],"its":[175],"from":[177],"unseen":[179],"deal":[182],"large":[184],"streams,":[186],"mini-batch":[190],"subgraph":[191],"sampling":[192],"strategy":[193],"scalable":[195],"training,":[196],"periodically":[198],"removes":[199],"obsolete":[200],"maintain":[203],"dynamic":[205],"embedding":[206],"space.":[207],"requires":[209],"no":[210],"feature":[211],"engineering":[212],"has":[214],"few":[215],"hyperparameters":[216],"tune.":[218],"Extensive":[219],"experiment":[220],"results":[221],"demonstrate":[222],"superiority":[224],"over":[227],"various":[228],"baselines.":[229]},"counts_by_year":[{"year":2026,"cited_by_count":9},{"year":2025,"cited_by_count":17},{"year":2024,"cited_by_count":15},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":18}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2021-02-01T00:00:00"}
