{"id":"https://openalex.org/W7161542526","doi":"https://doi.org/10.1145/3802044","title":"Efficient Anchored Densest Subgraph Discovery: Improved Time Complexity and Practical Performance","display_name":"Efficient Anchored Densest Subgraph Discovery: Improved Time Complexity and Practical Performance","publication_year":2026,"publication_date":"2026-05-18","ids":{"openalex":"https://openalex.org/W7161542526","doi":"https://doi.org/10.1145/3802044"},"language":"en","primary_location":{"id":"doi:10.1145/3802044","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3802044","pdf_url":null,"source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"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 ACM on Management of Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3802044","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5125179917","display_name":"Y K Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingli Zhou","raw_affiliation_strings":["The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0008-5630-6822","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061020754","display_name":"Youran Sun","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Youran Sun","raw_affiliation_strings":["The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0009-0005-1371-666X","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5136402529","display_name":"Yixiang Fang","orcid":"https://orcid.org/0000-0002-5047-8593"},"institutions":[{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yixiang Fang","raw_affiliation_strings":["The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China"],"raw_orcid":"https://orcid.org/0000-0002-5047-8593","affiliations":[{"raw_affiliation_string":"The Chinese University of Hong Kong, Shenzhen, Shenzhen, Guangdong, China","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210116924"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.60889314,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":"3","first_page":"1","last_page":"27"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.5257999897003174,"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":0.5257999897003174,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.20720000565052032,"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":0.09120000153779984,"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/graph","display_name":"Graph","score":0.5317000150680542},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.46939998865127563},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.4632999897003174},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.4269999861717224},{"id":"https://openalex.org/keywords/efficient-algorithm","display_name":"Efficient algorithm","score":0.41019999980926514},{"id":"https://openalex.org/keywords/knowledge-graph","display_name":"Knowledge graph","score":0.38519999384880066},{"id":"https://openalex.org/keywords/running-time","display_name":"Running time","score":0.3824999928474426}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6092000007629395},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5317000150680542},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.4767000079154968},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.46939998865127563},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.4632999897003174},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C3018263672","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Efficient algorithm","level":2,"score":0.41019999980926514},{"id":"https://openalex.org/C2987255567","wikidata":"https://www.wikidata.org/wiki/Q33002955","display_name":"Knowledge graph","level":2,"score":0.38519999384880066},{"id":"https://openalex.org/C3017489831","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Running time","level":2,"score":0.3824999928474426},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37619999051094055},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C191241153","wikidata":"https://www.wikidata.org/wiki/Q6027240","display_name":"Induced subgraph isomorphism problem","level":5,"score":0.3418999910354614},{"id":"https://openalex.org/C88230418","wikidata":"https://www.wikidata.org/wiki/Q131476","display_name":"Graph theory","level":2,"score":0.33809998631477356},{"id":"https://openalex.org/C131992880","wikidata":"https://www.wikidata.org/wiki/Q2528185","display_name":"Subgraph isomorphism problem","level":3,"score":0.3285999894142151},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3093999922275543},{"id":"https://openalex.org/C125583679","wikidata":"https://www.wikidata.org/wiki/Q755673","display_name":"Search algorithm","level":2,"score":0.29330000281333923},{"id":"https://openalex.org/C128115575","wikidata":"https://www.wikidata.org/wiki/Q5597083","display_name":"Graph factorization","level":5,"score":0.2653000056743622}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3802044","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3802044","pdf_url":null,"source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"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 ACM on Management of Data","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3802044","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3802044","pdf_url":null,"source":{"id":"https://openalex.org/S4387289859","display_name":"Proceedings of the ACM on Management of Data","issn_l":"2836-6573","issn":["2836-6573"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"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 ACM on Management of Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1500512125","https://openalex.org/W1888358353","https://openalex.org/W1898392233","https://openalex.org/W1921746303","https://openalex.org/W1924929788","https://openalex.org/W1983383464","https://openalex.org/W2020319151","https://openalex.org/W2051109346","https://openalex.org/W2121020155","https://openalex.org/W2169088933","https://openalex.org/W2170569385","https://openalex.org/W2207622687","https://openalex.org/W2217968126","https://openalex.org/W2259724869","https://openalex.org/W2266714125","https://openalex.org/W2620706275","https://openalex.org/W2939050176","https://openalex.org/W2953102514","https://openalex.org/W2962788915","https://openalex.org/W2970828623","https://openalex.org/W2982394413","https://openalex.org/W3004777475","https://openalex.org/W3034471508","https://openalex.org/W3046691040","https://openalex.org/W3130246349","https://openalex.org/W3174460405","https://openalex.org/W3212747350","https://openalex.org/W4224214728","https://openalex.org/W4312389781","https://openalex.org/W4380433246","https://openalex.org/W4381327380","https://openalex.org/W4383749545","https://openalex.org/W4385318193","https://openalex.org/W4392453911","https://openalex.org/W4393085118","https://openalex.org/W4396893083","https://openalex.org/W4401863545","https://openalex.org/W4402042827","https://openalex.org/W4402969637","https://openalex.org/W4409219065","https://openalex.org/W4413985126","https://openalex.org/W4417070810"],"related_works":[],"abstract_inverted_index":{"Densest":[0],"subgraph":[1,24,32],"discovery":[2],"(DSD)":[3],"is":[4,34,64],"a":[5,16,30,86,113,123],"fundamental":[6],"research":[7],"topic":[8],"in":[9,50,77],"network":[10],"science":[11],"and":[12,58,74],"graph":[13,114],"databases.":[14],"As":[15],"typical":[17],"variant":[18],"of":[19,151,171],"DSD,":[20],"the":[21,61,95,119,175],"anchored":[22,35],"densest":[23,31],"(ADS)":[25],"problem":[26,42,63],"aims":[27],"to":[28,46,122,168],"detect":[29],"that":[33,117,162],"around":[36],"user-defined":[37],"seed":[38],"vertices.":[39],"The":[40,159],"ADS":[41,62,120],"has":[43],"been":[44],"shown":[45],"be":[47],"very":[48,65],"useful":[49],"some":[51],"personalized":[52],"applications,":[53],"such":[54],"as":[55,98],"community":[56],"search":[57,121],"recommendation.":[59],"While":[60],"useful,":[66],"existing":[67,99],"algorithms":[68,165],"suffer":[69],"from":[70],"weak":[71],"theoretical":[72,131],"guarantees":[73],"perform":[75],"poorly":[76],"practice.":[78],"To":[79,106],"address":[80],"these":[81],"issues,":[82],"we":[83,111,137],"first":[84],"propose":[85],"novel":[87],"approximation":[88],"algorithm":[89],"with":[90],"improved":[91],"time":[92],"complexity,":[93],"achieving":[94],"same":[96],"accuracy":[97],"methods":[100],"while":[101,127],"requiring":[102],"significantly":[103],"fewer":[104],"iterations.":[105],"further":[107],"enhance":[108],"practical":[109],"performance,":[110],"introduce":[112],"reduction":[115],"technique":[116],"localizes":[118],"much":[124],"smaller":[125],"subgraph,":[126],"still":[128],"providing":[129],"non-trivial":[130],"guarantees.":[132],"Building":[133],"on":[134,154],"this":[135],"approximation,":[136],"also":[138],"develop":[139],"an":[140,147],"efficient":[141],"exact":[142],"algorithm.":[143],"We":[144],"have":[145],"performed":[146],"extensive":[148],"empirical":[149],"evaluation":[150],"our":[152,163],"approaches":[153],"12":[155],"real":[156],"large":[157],"datasets.":[158],"results":[160],"show":[161],"proposed":[164],"are":[166],"up":[167],"four":[169],"orders":[170],"magnitude":[172],"faster":[173],"than":[174],"state-of-the-art.":[176]},"counts_by_year":[],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2026-05-19T00:00:00"}