{"id":"https://openalex.org/W4417131090","doi":"https://doi.org/10.1109/tkde.2025.3639305","title":"BOTBIN: Accelerated Indexing for Structural Graph Clustering on Dynamic Graphs","display_name":"BOTBIN: Accelerated Indexing for Structural Graph Clustering on Dynamic Graphs","publication_year":2025,"publication_date":"2025-12-08","ids":{"openalex":"https://openalex.org/W4417131090","doi":"https://doi.org/10.1109/tkde.2025.3639305"},"language":null,"primary_location":{"id":"doi:10.1109/tkde.2025.3639305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3639305","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-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/A5100720406","display_name":"Fangyuan Zhang","orcid":"https://orcid.org/0009-0004-3253-4661"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Fangyuan Zhang","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, SAR, China","Chinese University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0009-0004-3253-4661","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, SAR, China","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009527915","display_name":"Qintian Guo","orcid":"https://orcid.org/0000-0001-9581-9817"},"institutions":[{"id":"https://openalex.org/I200769079","display_name":"Hong Kong University of Science and Technology","ror":"https://ror.org/00q4vv597","country_code":"HK","type":"education","lineage":["https://openalex.org/I200769079"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Qintian Guo","raw_affiliation_strings":["The Hong Kong University of Science and Technology, Hong Kong, SAR, China","The Hong Kong University of Science and Technology, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0001-9581-9817","affiliations":[{"raw_affiliation_string":"The Hong Kong University of Science and Technology, Hong Kong, SAR, China","institution_ids":["https://openalex.org/I200769079"]},{"raw_affiliation_string":"The Hong Kong University of Science and Technology, Hong Kong","institution_ids":["https://openalex.org/I200769079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068471095","display_name":"Junhao Gan","orcid":"https://orcid.org/0000-0001-9101-1503"},"institutions":[{"id":"https://openalex.org/I165779595","display_name":"The University of Melbourne","ror":"https://ror.org/01ej9dk98","country_code":"AU","type":"education","lineage":["https://openalex.org/I165779595"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Junhao Gan","raw_affiliation_strings":["The University of Melbourne, Parkville, VIC, Australia","University of Melbourne, Australia"],"raw_orcid":"https://orcid.org/0000-0001-9101-1503","affiliations":[{"raw_affiliation_string":"The University of Melbourne, Parkville, VIC, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"University of Melbourne, Australia","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100736050","display_name":"Sibo Wang","orcid":"https://orcid.org/0000-0003-1892-6971"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Sibo Wang","raw_affiliation_strings":["The Chinese University of Hong Kong, Hong Kong, SAR, China","Chinese University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0003-1892-6971","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong, SAR, China","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.34940615,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"38","issue":"2","first_page":"911","last_page":"928"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.4627000093460083,"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"}},"topics":[{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.4627000093460083,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.21699999272823334,"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":0.11309999972581863,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.8197000026702881},{"id":"https://openalex.org/keywords/jaccard-index","display_name":"Jaccard index","score":0.6779999732971191},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.5770000219345093},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.47130000591278076},{"id":"https://openalex.org/keywords/canopy-clustering-algorithm","display_name":"Canopy clustering algorithm","score":0.4361000061035156},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4275999963283539},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.42649999260902405},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.4235000014305115},{"id":"https://openalex.org/keywords/vertex","display_name":"Vertex (graph theory)","score":0.4074999988079071}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8197000026702881},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.733299970626831},{"id":"https://openalex.org/C203519979","wikidata":"https://www.wikidata.org/wiki/Q865360","display_name":"Jaccard index","level":3,"score":0.6779999732971191},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.5770000219345093},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.47130000591278076},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43970000743865967},{"id":"https://openalex.org/C104047586","wikidata":"https://www.wikidata.org/wiki/Q5033439","display_name":"Canopy clustering algorithm","level":4,"score":0.4361000061035156},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4275999963283539},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.42649999260902405},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.4235000014305115},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4174000024795532},{"id":"https://openalex.org/C80899671","wikidata":"https://www.wikidata.org/wiki/Q1304193","display_name":"Vertex (graph theory)","level":3,"score":0.4074999988079071},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.35530000925064087},{"id":"https://openalex.org/C193143536","wikidata":"https://www.wikidata.org/wiki/Q5227360","display_name":"Data stream clustering","level":5,"score":0.33719998598098755},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3330000042915344},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.33009999990463257},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.3273000121116638},{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3086000084877014},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C27964816","wikidata":"https://www.wikidata.org/wiki/Q5164359","display_name":"Constrained clustering","level":5,"score":0.2921000123023987},{"id":"https://openalex.org/C162319229","wikidata":"https://www.wikidata.org/wiki/Q175263","display_name":"Data structure","level":2,"score":0.28439998626708984},{"id":"https://openalex.org/C99580578","wikidata":"https://www.wikidata.org/wiki/Q5319002","display_name":"Dynamic problem","level":2,"score":0.2736000120639801},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2639000117778778}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2025.3639305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2025.3639305","pdf_url":null,"source":{"id":"https://openalex.org/S30698027","display_name":"IEEE Transactions on Knowledge and Data Engineering","issn_l":"1041-4347","issn":["1041-4347","1558-2191","2326-3865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320439","host_organization_name":"IEEE Computer Society","host_organization_lineage":["https://openalex.org/P4310320439","https://openalex.org/P4310319808"],"host_organization_lineage_names":["IEEE Computer Society","Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Knowledge and Data Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334704","display_name":"Australian Research Council","ror":"https://ror.org/05mmh0f86"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1455310343","https://openalex.org/W1561458624","https://openalex.org/W1566772816","https://openalex.org/W1667863317","https://openalex.org/W1977236339","https://openalex.org/W1979819093","https://openalex.org/W1981915380","https://openalex.org/W1981974552","https://openalex.org/W1995528370","https://openalex.org/W1997871231","https://openalex.org/W2002517322","https://openalex.org/W2007954020","https://openalex.org/W2017987256","https://openalex.org/W2021845466","https://openalex.org/W2033390315","https://openalex.org/W2048744899","https://openalex.org/W2074986735","https://openalex.org/W2084979067","https://openalex.org/W2088840018","https://openalex.org/W2104382693","https://openalex.org/W2127048411","https://openalex.org/W2128056631","https://openalex.org/W2134008243","https://openalex.org/W2142140138","https://openalex.org/W2165186823","https://openalex.org/W2165515835","https://openalex.org/W2243560673","https://openalex.org/W2346638866","https://openalex.org/W2573735949","https://openalex.org/W2615250859","https://openalex.org/W2800142148","https://openalex.org/W2885972824","https://openalex.org/W2898126971","https://openalex.org/W2901711611","https://openalex.org/W2962733107","https://openalex.org/W3114289308","https://openalex.org/W3173235128","https://openalex.org/W4232226726","https://openalex.org/W4312839977","https://openalex.org/W4380433272"],"related_works":[],"abstract_inverted_index":{"Graph":[0],"clustering":[1,17,28,34,53,83,112,153,212,244,283],"is":[2,23,89,147,177,203,266],"a":[3,24,120,180,204],"fundamental":[4],"data":[5],"mining":[6],"task":[7],"that":[8,30,190,207,223,263],"clusters":[9],"vertices":[10,41,195,217],"into":[11],"different":[12],"groups.":[13],"The":[14,60,175,200],"structural":[15,51,81],"graph":[16,27,52,82],"algorithm":[18,29,84,129,226],"(<inline-formula":[19],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[20,182,229,249,256],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[21,183,230,250,257],"notation=\"LaTeX\">$SCAN$</tex-math></inline-formula>)":[22],"widely":[25],"used":[26],"derives":[31],"not":[32,159],"only":[33],"results,":[35],"but":[36],"also":[37],"special":[38],"roles":[39,215],"of":[40,102,193,216,271],"like":[42],"hubs":[43],"and":[44,68,214,239],"outliers.":[45],"In":[46],"this":[47],"paper,":[48],"we":[49,118],"consider":[50],"on":[54,65,122,130],"dynamic":[55,80,131,137],"graphs":[56,67],"under":[57,86],"Jaccard":[58,87],"similarity.":[59],"state-of-the-art":[61,136,276],"index-based":[62,277],"solution":[63,93,157,170,265,278],"focuses":[64],"static":[66],"incurs":[69],"prohibitive":[70],"update":[71,211,237],"costs":[72],"to":[73,95,106,109,134,142,152,161,178,210,241,254,268],"maintain":[74,179],"indices.":[75],"Lately,":[76],"an":[77],"efficient":[78],"approximate":[79,243],"DynStrClu":[85],"similarity":[88],"proposed.":[90],"However,":[91,155],"their":[92],"needs":[94],"fix":[96,162],"input":[97,164],"parameters":[98],"while":[99,279],"parameter":[100],"settings":[101],"SCAN":[103,128],"usually":[104],"need":[105,160],"be":[107,197],"fine-tuned":[108],"achieve":[110,167],"good":[111],"results.":[113,154,284],"Motivated":[114],"by":[115,149],"these":[116],"limitations,":[117],"present":[119],"study":[121],"devising":[123],"effective":[124],"index":[125],"structures":[126],"for":[127,186],"graphs.":[132],"Similar":[133],"the":[135,144,163,191,275],"scheme,":[138],"our":[139,156,169,224,264],"main":[140],"idea":[141],"reduce":[143],"time":[145],"complexity":[146],"still":[148,280],"bringing":[150],"approximation":[151],"does":[158],"parameters.":[165],"To":[166],"this,":[168],"includes":[171],"two":[172,269],"key":[173,202],"components.":[174],"first":[176],"bottom-<inline-formula":[181],"notation=\"LaTeX\">$k$</tex-math></inline-formula>":[184],"sketch":[185],"each":[187],"vertex":[188],"so":[189],"similarities":[192],"affected":[194],"can":[196],"easily":[198],"updated.":[199],"second":[201],"bucketing":[205],"strategy":[206],"allows":[208],"us":[209],"results":[213,245],"efficiently.":[218],"Our":[219],"theoretical":[220],"analysis":[221],"shows":[222],"proposed":[225],"achieves":[227],"<inline-formula":[228,248,255],"notation=\"LaTeX\">$O(\\log":[231],"\\log":[232,234],"{\\frac{M+m}{p_{f}}}\\cdot":[233],"{\\frac{M+m}{p_{f}}})$</tex-math></inline-formula>":[235],"expected":[236],"cost":[238],"guarantees":[240],"return":[242],"with":[246],"probability":[247],"notation=\"LaTeX\">$1-p_{f}$</tex-math></inline-formula>":[251],"after":[252],"up":[253,267],"notation=\"LaTeX\">$M$</tex-math></inline-formula>":[258],"updates.":[259],"Extensive":[260],"experiments":[261],"show":[262],"orders":[270],"magnitude":[272],"faster":[273],"than":[274],"achieving":[281],"high-quality":[282]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-12-08T00:00:00"}