{"id":"https://openalex.org/W4384519032","doi":"https://doi.org/10.1109/tkde.2023.3272574","title":"Unified Dense Subgraph Detection: Fast Spectral Theory Based Algorithms","display_name":"Unified Dense Subgraph Detection: Fast Spectral Theory Based Algorithms","publication_year":2023,"publication_date":"2023-07-17","ids":{"openalex":"https://openalex.org/W4384519032","doi":"https://doi.org/10.1109/tkde.2023.3272574"},"language":"en","primary_location":{"id":"doi:10.1109/tkde.2023.3272574","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2023.3272574","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/A5052227670","display_name":"Wenjie Feng","orcid":"https://orcid.org/0000-0003-3636-0035"},"institutions":[{"id":"https://openalex.org/I165932596","display_name":"National University of Singapore","ror":"https://ror.org/01tgyzw49","country_code":"SG","type":"education","lineage":["https://openalex.org/I165932596"]},{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN","SG"],"is_corresponding":false,"raw_author_name":"Wenjie Feng","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","Institute of Data Science, National University of Singapore, Singapore"],"raw_orcid":"https://orcid.org/0000-0003-3636-0035","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]},{"raw_affiliation_string":"Institute of Data Science, National University of Singapore, Singapore","institution_ids":["https://openalex.org/I165932596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100677836","display_name":"Shenghua Liu","orcid":"https://orcid.org/0000-0003-2120-3598"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shenghua Liu","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-2120-3598","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015996266","display_name":"Danai Koutra","orcid":"https://orcid.org/0000-0002-3206-8179"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danai Koutra","raw_affiliation_strings":["University of Michigan, Ann Arbor, MI, USA"],"raw_orcid":"https://orcid.org/0000-0002-3206-8179","affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, MI, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029998682","display_name":"Xueqi Cheng","orcid":"https://orcid.org/0000-0002-5201-8195"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xueqi Cheng","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-5201-8195","affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4903,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.59002854,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":"36","issue":"3","first_page":"1356","last_page":"1370"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12292","display_name":"Graph Theory and Algorithms","score":0.9950000047683716,"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":0.9950000047683716,"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/T10799","display_name":"Data Visualization and Analytics","score":0.9901999831199646,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9886000156402588,"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":0.7537294626235962},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5965084433555603}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7537294626235962},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5965084433555603}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tkde.2023.3272574","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tkde.2023.3272574","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":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.6499999761581421}],"awards":[{"id":"https://openalex.org/G2706053043","display_name":null,"funder_award_id":"62377043","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3167315294","display_name":null,"funder_award_id":"U1911401","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G740642855","display_name":null,"funder_award_id":"U21B2046","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8474963640","display_name":"\u9762\u5411\u5927\u6570\u636e\u667a\u80fd\u5904\u7406\u7684\u968f\u673a\u77e9\u9635\u4e0e\u5f20\u91cf\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61872206","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":86,"referenced_works":["https://openalex.org/W75795297","https://openalex.org/W183656749","https://openalex.org/W348531675","https://openalex.org/W1482680420","https://openalex.org/W1535144194","https://openalex.org/W1560607100","https://openalex.org/W1589703745","https://openalex.org/W1888358353","https://openalex.org/W1910316331","https://openalex.org/W1924929788","https://openalex.org/W1964043357","https://openalex.org/W1975308300","https://openalex.org/W2006820476","https://openalex.org/W2009339416","https://openalex.org/W2013469283","https://openalex.org/W2020742901","https://openalex.org/W2028753055","https://openalex.org/W2032279394","https://openalex.org/W2047923585","https://openalex.org/W2054560566","https://openalex.org/W2086254934","https://openalex.org/W2086805702","https://openalex.org/W2089554624","https://openalex.org/W2090775786","https://openalex.org/W2093690536","https://openalex.org/W2096361430","https://openalex.org/W2117756735","https://openalex.org/W2119757574","https://openalex.org/W2120595041","https://openalex.org/W2121947440","https://openalex.org/W2132914434","https://openalex.org/W2133591726","https://openalex.org/W2151936673","https://openalex.org/W2153291291","https://openalex.org/W2170432751","https://openalex.org/W2217968126","https://openalex.org/W2248736178","https://openalex.org/W2259724869","https://openalex.org/W2260890852","https://openalex.org/W2266714125","https://openalex.org/W2294347342","https://openalex.org/W2348679751","https://openalex.org/W2364972310","https://openalex.org/W2479445230","https://openalex.org/W2586047314","https://openalex.org/W2605272442","https://openalex.org/W2743418339","https://openalex.org/W2744808284","https://openalex.org/W2747333531","https://openalex.org/W2755088640","https://openalex.org/W2767552592","https://openalex.org/W2767952030","https://openalex.org/W2808895435","https://openalex.org/W2896916493","https://openalex.org/W2897763116","https://openalex.org/W2900745741","https://openalex.org/W2912708407","https://openalex.org/W2935051602","https://openalex.org/W2944170995","https://openalex.org/W2953102514","https://openalex.org/W2963702719","https://openalex.org/W2970828623","https://openalex.org/W3012585669","https://openalex.org/W3022297969","https://openalex.org/W3022679923","https://openalex.org/W3032557024","https://openalex.org/W3032890203","https://openalex.org/W3035455649","https://openalex.org/W3046691040","https://openalex.org/W3094534277","https://openalex.org/W3106359669","https://openalex.org/W3124850851","https://openalex.org/W3137361208","https://openalex.org/W3152330821","https://openalex.org/W4206161257","https://openalex.org/W4242981398","https://openalex.org/W4250589301","https://openalex.org/W4312258136","https://openalex.org/W4312389781","https://openalex.org/W6604687372","https://openalex.org/W6607484853","https://openalex.org/W6639794280","https://openalex.org/W6682745898","https://openalex.org/W6703432866","https://openalex.org/W6730412671","https://openalex.org/W6744271739"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2051487156","https://openalex.org/W2073681303","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109"],"abstract_inverted_index":{"How":[0,13],"can":[1,14,27],"we":[2,15,28,65,85],"effectively":[3],"detect":[4],"fake":[5],"reviews":[6],"or":[7,165],"fraudulent":[8],"links":[9],"on":[10,22,67,102,136],"a":[11,35,49,87],"website?":[12],"spot":[16],"communities":[17],"that":[18,151,210],"suddenly":[19,212],"appear":[20,211],"based":[21,101],"users\u2019":[23],"interactions?":[24],"And":[25],"how":[26],"efficiently":[29],"find":[30],"the":[31,44,69,72,93,103,126,170,176,188,197],"minimum":[32],"cut":[33],"in":[34,53,204,213],"large":[36],"graph?":[37],"All":[38],"of":[39,46,71,183],"these":[40],"are":[41,201],"related":[42],"to":[43,121,142,156,175],"finding":[45,208],"dense":[47],"subgraphs,":[48],"significant":[50],"primitive":[51],"problem":[52,70],"graph":[54,108,198],"analysis":[55,100],"with":[56,140,196],"extensive":[57],"applications":[58,205],"across":[59],"various":[60,147],"domains.":[61,148],"In":[62],"this":[63],"paper,":[64],"focus":[66],"formulating":[68],"densest":[73,94,171],"subgraph":[74,95,172],"detection":[75,173],"and":[76,79,106,110,113,118,129,162,200],"theoretically":[77],"compare":[78],"contrast":[80],"several":[81],"correlated":[82],"problems.":[83],"Moreover,":[84],"propose":[86],"unified":[88],"framework,":[89],"<small>GenDS</small>":[90,189],",":[91,120],"for":[92,169,187],"detection,":[96],"provide":[97],"some":[98,181],"theoretical":[99],"network":[104],"flow":[105],"spectral":[107,127],"theory,":[109],"devise":[111],"simple":[112],"computationally":[114],"efficient":[115],"algorithms,":[116],"<small>SpecGDS</small>":[117,153],"<small>GepGDS</small>":[119,178],"solve":[122],"it":[123],"by":[124],"leveraging":[125],"properties":[128,182],"greedy":[130],"search.":[131],"We":[132,149],"conduct":[133],"thorough":[134],"experiments":[135],"40":[137],"real-world":[138],"networks":[139],"up":[141,155],"1.47":[143],"billion":[144],"edges":[145],"from":[146],"demonstrate":[150],"our":[152,192],"yields":[154],"<inline-formula><tex-math":[157],"notation=\"LaTeX\">$58.6":[158],"\\":[159],"\\times$</tex-math></inline-formula>":[160],"speedup":[161],"achieves":[163],"better":[164],"approximately":[166],"equal-quality":[167],"solutions":[168],"compared":[174],"baselines.":[177],"also":[179],"reveals":[180],"generalized":[184],"eigenvalue":[185],"problems":[186],".":[190],"Also,":[191],"methods":[193],"scale":[194],"linearly":[195],"size":[199],"proven":[202],"effective":[203],"such":[206],"as":[207],"collaborations":[209],"an":[214],"extensive,":[215],"time-evolving":[216],"co-authorship":[217],"network.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":3}],"updated_date":"2026-07-17T09:13:05.818461","created_date":"2025-10-10T00:00:00"}