{"id":"https://openalex.org/W4406458446","doi":"https://doi.org/10.1109/bigdata62323.2024.10825777","title":"Introducing the Converse k-clustering Problem","display_name":"Introducing the Converse k-clustering Problem","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406458446","doi":"https://doi.org/10.1109/bigdata62323.2024.10825777"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825777","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825777","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-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/A5110667925","display_name":"Byron J. Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Byron J. Gao","raw_affiliation_strings":["Texas State University,Department of Computer Science,San Marcos,USA"],"affiliations":[{"raw_affiliation_string":"Texas State University,Department of Computer Science,San Marcos,USA","institution_ids":["https://openalex.org/I13511017"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5110667925"],"corresponding_institution_ids":["https://openalex.org/I13511017"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.30667601,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8658","last_page":"8660"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T10720","display_name":"Complexity and Algorithms in Graphs","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/1703","display_name":"Computational Theory and Mathematics"},"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/T11502","display_name":"Facility Location and Emergency Management","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1407","display_name":"Organizational Behavior and Human Resource Management"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10567","display_name":"Vehicle Routing Optimization Methods","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/converse","display_name":"Converse","score":0.8756197094917297},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.7034772634506226},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6129549145698547},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.25711971521377563},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24201297760009766}],"concepts":[{"id":"https://openalex.org/C2776809875","wikidata":"https://www.wikidata.org/wiki/Q1375963","display_name":"Converse","level":2,"score":0.8756197094917297},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.7034772634506226},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6129549145698547},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.25711971521377563},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24201297760009766},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825777","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825777","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1523265685","https://openalex.org/W1558127485","https://openalex.org/W1602828742","https://openalex.org/W1969972789","https://openalex.org/W1990313671","https://openalex.org/W2011039300","https://openalex.org/W2038933051","https://openalex.org/W2056090079","https://openalex.org/W2088659184","https://openalex.org/W2128193809","https://openalex.org/W2167036627","https://openalex.org/W2560674852","https://openalex.org/W2911226811","https://openalex.org/W3159723557"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2387449261","https://openalex.org/W2418518962","https://openalex.org/W2963377682","https://openalex.org/W2043159103","https://openalex.org/W2391769344","https://openalex.org/W2359260952","https://openalex.org/W4297790016"],"abstract_inverted_index":{"In":[0,101],"this":[1],"paper":[2,103],"we":[3,53,104],"introduce":[4],"the":[5,25,43,76,102],"converse":[6,59,73,122],"k-clustering":[7,60,74],"problem":[8],"as":[9,71,85,113],"an":[10],"alternative":[11],"partitional":[12],"clustering":[13,16,22],"model.":[14],"Partitional":[15],"is":[17,28,46],"a":[18,31,63,68],"traditional":[19],"category":[20],"of":[21,35,78],"methods,":[23],"where":[24],"general":[26],"formulation":[27],"to":[29,49,120],"produce":[30],"given":[32],"k":[33,45],"number":[34,77],"clusters":[36,79],"that":[37,55],"minimize":[38],"some":[39],"compactness":[40,69,82],"objective.":[41],"Since":[42],"parameter":[44],"often":[47],"hard":[48],"determine":[50],"in":[51,56,96],"advance,":[52],"argue":[54],"many":[57,97],"cases":[58],"can":[61,88,117],"be":[62,89,118],"more":[64],"appropriate":[65],"formulation.":[66],"Given":[67],"threshold":[70],"constraint,":[72],"minimizes":[75],"k.":[80],"Such":[81],"constraints,":[83],"such":[84,112],"maximum":[86],"diameter,":[87],"intuitively":[90],"specified":[91],"based":[92],"on":[93],"domain":[94],"knowledge":[95],"real":[98],"world":[99],"applications.":[100],"also":[105],"show":[106],"how":[107],"conventional":[108],"combinatorial":[109],"optimization":[110],"techniques,":[111],"minimum":[114],"clique":[115],"partition,":[116],"adapted":[119],"solve":[121],"k-clustering.":[123]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}