{"id":"https://openalex.org/W7152529609","doi":"https://doi.org/10.1145/3774904.3792116","title":"Scalable and Provable Biclique-Preserving Clustering: The Power of Counting-based Approaches","display_name":"Scalable and Provable Biclique-Preserving Clustering: The Power of Counting-based Approaches","publication_year":2026,"publication_date":"2026-04-09","ids":{"openalex":"https://openalex.org/W7152529609","doi":"https://doi.org/10.1145/3774904.3792116"},"language":null,"primary_location":{"id":"doi:10.1145/3774904.3792116","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792116","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 ACM Web Conference 2026","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3774904.3792116","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101021504","display_name":"Longlong Lin","orcid":"https://orcid.org/0000-0002-2194-8146"},"institutions":[{"id":"https://openalex.org/I142108993","display_name":"Southwest University","ror":"https://ror.org/01kj4z117","country_code":"CN","type":"education","lineage":["https://openalex.org/I142108993"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Longlong Lin","raw_affiliation_strings":["Southwest University, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-2194-8146","affiliations":[{"raw_affiliation_string":"Southwest University, Chongqing, China","institution_ids":["https://openalex.org/I142108993"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101397036","display_name":"Zeli Wang","orcid":"https://orcid.org/0000-0002-5053-5201"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zeli Wang","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-5053-5201","affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100742464","display_name":"Rong-Hua Li","orcid":"https://orcid.org/0000-0001-8658-6599"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong-Hua Li","raw_affiliation_strings":["Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8658-6599","affiliations":[{"raw_affiliation_string":"Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046092496","display_name":"Xiaohai Dai","orcid":"https://orcid.org/0000-0001-7822-4512"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohai Dai","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-7822-4512","affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100646551","display_name":"Ni Li","orcid":"https://orcid.org/0000-0003-0178-3839"},"institutions":[{"id":"https://openalex.org/I143868143","display_name":"Anhui University","ror":"https://ror.org/05th6yx34","country_code":"CN","type":"education","lineage":["https://openalex.org/I143868143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Ni","raw_affiliation_strings":["Anhui University, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0003-0178-3839","affiliations":[{"raw_affiliation_string":"Anhui University, Hefei, China","institution_ids":["https://openalex.org/I143868143"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102730151","display_name":"Jin Zhao","orcid":"https://orcid.org/0000-0003-4217-7886"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jin Zhao","raw_affiliation_strings":["Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-4217-7886","affiliations":[{"raw_affiliation_string":"Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"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":0.51772258,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"559","last_page":"570"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.7193999886512756,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.7193999886512756,"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/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.04309999942779541,"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/T11106","display_name":"Data Management and Algorithms","score":0.019500000402331352,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/scalability","display_name":"Scalability","score":0.5311999917030334},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.5212000012397766},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.34929999709129333},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.3443000018596649},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.3061999976634979}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6460000276565552},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5311999917030334},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.5212000012397766},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.34929999709129333},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.3443000018596649},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3222000002861023},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.3061999976634979},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2590000033378601}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3774904.3792116","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792116","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 ACM Web Conference 2026","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3774904.3792116","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3774904.3792116","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 ACM Web Conference 2026","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4662246108055115}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W1970463918","https://openalex.org/W2027684023","https://openalex.org/W2032273054","https://openalex.org/W2076248831","https://openalex.org/W2079535727","https://openalex.org/W2117311203","https://openalex.org/W2128366083","https://openalex.org/W2133576408","https://openalex.org/W2153624566","https://openalex.org/W2157762631","https://openalex.org/W2169223901","https://openalex.org/W2266294848","https://openalex.org/W2497037546","https://openalex.org/W2583803680","https://openalex.org/W2767249079","https://openalex.org/W2923996791","https://openalex.org/W2965557726","https://openalex.org/W2970828623","https://openalex.org/W2997197692","https://openalex.org/W3046691040","https://openalex.org/W3076192884","https://openalex.org/W3119582991","https://openalex.org/W3137062906","https://openalex.org/W3142348832","https://openalex.org/W3197093862","https://openalex.org/W4210757530","https://openalex.org/W4280595061","https://openalex.org/W4288070781","https://openalex.org/W4312258136","https://openalex.org/W4324087027","https://openalex.org/W4380433124","https://openalex.org/W4380433187","https://openalex.org/W4382240020","https://openalex.org/W4393212306","https://openalex.org/W4394685238","https://openalex.org/W4411270023","https://openalex.org/W4412170785","https://openalex.org/W4416010501","https://openalex.org/W7083022907"],"related_works":[],"abstract_inverted_index":{"Bipartite":[0],"graphs":[1,50],"are":[2,15,67,154],"widely":[3],"used":[4],"to":[5,42,60,108,133,160],"model":[6],"relationships":[7],"between":[8],"entities":[9],"of":[10,48,103,113],"different":[11],"types,":[12],"where":[13],"vertices":[14,137],"divided":[16],"into":[17],"two":[18],"disjoint":[19],"sets.":[20],"Biclique-preserving":[21],"clustering":[22,62],"is":[23,105],"a":[24,84],"fundamental":[25],"operation":[26],"that":[27,92,151],"retrieves":[28],"clusters":[29],"with":[30],"dense":[31],"bicliques,":[32],"enabling":[33],"various":[34],"emerging":[35],"applications.":[36],"However,":[37],"existing":[38,65],"methods":[39,66],"either":[40],"fail":[41],"accurately":[43],"capture":[44],"the":[45,54,135,142],"unique":[46],"properties":[47],"bipartite":[49],"or":[51],"significantly":[52,116],"overlook":[53],"informative":[55],"higher-order":[56],"biclique":[57,71],"substructure,":[58],"leading":[59],"compromised":[61],"quality.":[63],"Additionally,":[64],"overly":[68],"dependent":[69],"on":[70,147],"enumeration,":[72,115],"resulting":[73],"in":[74],"poor":[75],"scalability.":[76],"To":[77,122],"address":[78],"these":[79],"challenges,":[80],"we":[81,126],"propose":[82,127],"ECRC,":[83],"simple":[85],"yet":[86],"provable":[87],"Edge-Centric":[88],"Reweighting":[89],"Clustering":[90],"framework":[91],"provides":[93],"strict":[94],"approximation":[95],"guarantees":[96],"for":[97],"any":[98],"biclique.":[99],"A":[100],"key":[101],"advantage":[102],"ECRC":[104],"its":[106],"ability":[107],"leverage":[109],"powerful":[110],"counting":[111],"instead":[112],"exhaustive":[114],"reducing":[117],"time":[118],"and":[119,138,157],"space":[120],"complexity.":[121],"further":[123],"improve":[124],"efficiency,":[125],"several":[128],"effective":[129,158],"graph":[130],"reduction":[131],"strategies":[132],"eliminate":[134],"unqualified":[136],"edges":[139],"before":[140],"calculating":[141],"edge-centric":[143],"weight.":[144],"Extensive":[145],"experiments":[146],"five":[148],"datasets":[149],"show":[150],"our":[152],"algorithms":[153],"more":[155],"efficient":[156],"compared":[159],"six":[161],"baselines.":[162]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-10T00:00:00"}