{"id":"https://openalex.org/W3035789548","doi":"https://doi.org/10.1145/3394486.3403238","title":"Parameterized Correlation Clustering in Hypergraphs and Bipartite Graphs","display_name":"Parameterized Correlation Clustering in Hypergraphs and Bipartite Graphs","publication_year":2020,"publication_date":"2020-08-20","ids":{"openalex":"https://openalex.org/W3035789548","doi":"https://doi.org/10.1145/3394486.3403238","mag":"3035789548"},"language":"en","primary_location":{"id":"doi:10.1145/3394486.3403238","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3394486.3403238","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3394486.3403238","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3394486.3403238","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5046315164","display_name":"Nate Veldt","orcid":"https://orcid.org/0000-0002-0117-3304"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nate Veldt","raw_affiliation_strings":["Cornell University, Ithaca, NY, USA","cornell University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]},{"raw_affiliation_string":"cornell University","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087794199","display_name":"Anthony Wirth","orcid":"https://orcid.org/0000-0003-3746-6704"},"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":"Anthony Wirth","raw_affiliation_strings":["The University of Melbourne, Melbourne, VIC, Australia","University of Melbourne"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Melbourne, Melbourne, VIC, Australia","institution_ids":["https://openalex.org/I165779595"]},{"raw_affiliation_string":"University of Melbourne","institution_ids":["https://openalex.org/I165779595"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084102378","display_name":"David F. Gleich","orcid":"https://orcid.org/0000-0002-8107-6474"},"institutions":[{"id":"https://openalex.org/I219193219","display_name":"Purdue University West Lafayette","ror":"https://ror.org/02dqehb95","country_code":"US","type":"education","lineage":["https://openalex.org/I219193219"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David F. Gleich","raw_affiliation_strings":["Purdue University, West Lafayette, IN, USA","PURDUE UNIVERSITY"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Purdue University, West Lafayette, IN, USA","institution_ids":["https://openalex.org/I219193219"]},{"raw_affiliation_string":"PURDUE UNIVERSITY","institution_ids":["https://openalex.org/I219193219"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2598,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.50805055,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1868","last_page":"1876"},"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9879000186920166,"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/T10887","display_name":"Bioinformatics and Genomic Networks","score":0.965499997138977,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/bipartite-graph","display_name":"Bipartite graph","score":0.8576854467391968},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.8215147256851196},{"id":"https://openalex.org/keywords/hypergraph","display_name":"Hypergraph","score":0.7579836845397949},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.631064236164093},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.5223351716995239},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5144848823547363},{"id":"https://openalex.org/keywords/time-complexity","display_name":"Time complexity","score":0.5132644176483154},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.48220694065093994},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.47524213790893555},{"id":"https://openalex.org/keywords/approximation-algorithm","display_name":"Approximation algorithm","score":0.4284575879573822},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4153960049152374},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3811878561973572},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.3441528081893921},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.33222174644470215},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3312816023826599},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.2465115487575531}],"concepts":[{"id":"https://openalex.org/C197657726","wikidata":"https://www.wikidata.org/wiki/Q174733","display_name":"Bipartite graph","level":3,"score":0.8576854467391968},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.8215147256851196},{"id":"https://openalex.org/C2781221856","wikidata":"https://www.wikidata.org/wiki/Q840247","display_name":"Hypergraph","level":2,"score":0.7579836845397949},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.631064236164093},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.5223351716995239},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5144848823547363},{"id":"https://openalex.org/C311688","wikidata":"https://www.wikidata.org/wiki/Q2393193","display_name":"Time complexity","level":2,"score":0.5132644176483154},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.48220694065093994},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.47524213790893555},{"id":"https://openalex.org/C148764684","wikidata":"https://www.wikidata.org/wiki/Q621751","display_name":"Approximation algorithm","level":2,"score":0.4284575879573822},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4153960049152374},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3811878561973572},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.3441528081893921},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.33222174644470215},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3312816023826599},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.2465115487575531},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1145/3394486.3403238","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3394486.3403238","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3394486.3403238","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2002.09460","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2002.09460","pdf_url":"https://arxiv.org/pdf/2002.09460","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":"","raw_type":"text"},{"id":"mag:3035789548","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/2002.09460.pdf","pdf_url":null,"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":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2002.09460","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2002.09460","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.1145/3394486.3403238","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3394486.3403238","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3394486.3403238","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1368711359","display_name":"BIGDATA: F: Models, Algorithms, and Software for Spatial-Relational Networks","funder_award_id":"1546488","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1515239336","display_name":null,"funder_award_id":"IIS-1546488","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1547680671","display_name":null,"funder_award_id":"IIS-1546488, CCF-1909528, CCF-0939370","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G1739869781","display_name":null,"funder_award_id":"CCF-0939370","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6244900323","display_name":"Emerging Frontiers of Science of Information","funder_award_id":"0939370","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6270065602","display_name":"AF: Small: Collaborative Research: An Investigation of Richer Conductance Measures for Real-World Graphs","funder_award_id":"1909528","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6322925478","display_name":null,"funder_award_id":"CCF-1909528","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"},{"id":"https://openalex.org/G8328576242","display_name":"FAULT OBLIVIOUS COMPUTATIONS","funder_award_id":"DESC0014543","funder_id":"https://openalex.org/F4320306084","funder_display_name":"U.S. Department of Energy"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320306084","display_name":"U.S. Department of Energy","ror":"https://ror.org/01bj3aw27"},{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"},{"id":"https://openalex.org/F4320306151","display_name":"Alfred P. Sloan Foundation","ror":"https://ror.org/052csg198"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3035789548.pdf","grobid_xml":"https://content.openalex.org/works/W3035789548.grobid-xml"},"referenced_works_count":55,"referenced_works":["https://openalex.org/W1648113946","https://openalex.org/W1973113780","https://openalex.org/W1974906551","https://openalex.org/W1976702945","https://openalex.org/W1982119153","https://openalex.org/W1985875030","https://openalex.org/W1988153470","https://openalex.org/W1992107140","https://openalex.org/W2033947830","https://openalex.org/W2044988896","https://openalex.org/W2070232376","https://openalex.org/W2071234528","https://openalex.org/W2091858563","https://openalex.org/W2095293504","https://openalex.org/W2107223449","https://openalex.org/W2108614537","https://openalex.org/W2109220922","https://openalex.org/W2120901716","https://openalex.org/W2121947440","https://openalex.org/W2128366083","https://openalex.org/W2131681506","https://openalex.org/W2135957668","https://openalex.org/W2140360868","https://openalex.org/W2142184646","https://openalex.org/W2146081992","https://openalex.org/W2148070710","https://openalex.org/W2153873308","https://openalex.org/W2157762631","https://openalex.org/W2158579916","https://openalex.org/W2170057991","https://openalex.org/W2170734407","https://openalex.org/W2513567506","https://openalex.org/W2560745921","https://openalex.org/W2605850919","https://openalex.org/W2743418339","https://openalex.org/W2811503669","https://openalex.org/W2893274952","https://openalex.org/W2912935170","https://openalex.org/W2914959486","https://openalex.org/W2948499415","https://openalex.org/W2951153688","https://openalex.org/W2962752269","https://openalex.org/W2962935106","https://openalex.org/W2963361089","https://openalex.org/W2963815604","https://openalex.org/W2971196067","https://openalex.org/W2973019811","https://openalex.org/W2983727063","https://openalex.org/W2991187137","https://openalex.org/W2999163148","https://openalex.org/W3006154861","https://openalex.org/W3098765153","https://openalex.org/W3104252707","https://openalex.org/W4234920499","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W3080755825","https://openalex.org/W3008027580","https://openalex.org/W3152772521","https://openalex.org/W2991187137","https://openalex.org/W3201171444","https://openalex.org/W3081374773","https://openalex.org/W2900031086","https://openalex.org/W3106228791","https://openalex.org/W2560576693","https://openalex.org/W2788362011","https://openalex.org/W3099517909","https://openalex.org/W1967761844","https://openalex.org/W2752425240","https://openalex.org/W2303006504","https://openalex.org/W2295225727","https://openalex.org/W2767952030","https://openalex.org/W1965656937","https://openalex.org/W2952712772","https://openalex.org/W2975614804","https://openalex.org/W3167661096"],"abstract_inverted_index":{"Motivated":[0],"by":[1,24],"applications":[2],"in":[3,15,30,37],"community":[4],"detection":[5],"and":[6,17],"dense":[7],"subgraph":[8],"discovery,":[9],"we":[10],"consider":[11],"new":[12],"clustering":[13],"objectives":[14,21],"hypergraphs":[16],"bipartite":[18],"graphs.":[19],"These":[20],"are":[22],"parameterized":[23],"one":[25],"or":[26],"more":[27],"resolution":[28],"parameters":[29],"order":[31],"to":[32],"enable":[33],"diverse":[34],"knowledge":[35],"discovery":[36],"complex":[38],"data.":[39]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-07-07T14:30:12.667765","created_date":"2025-10-10T00:00:00"}