{"id":"https://openalex.org/W4224322513","doi":"https://doi.org/10.1145/3485447.3512188","title":"Fair k-Center Clustering in MapReduce and Streaming Settings","display_name":"Fair k-Center Clustering in MapReduce and Streaming Settings","publication_year":2022,"publication_date":"2022-04-25","ids":{"openalex":"https://openalex.org/W4224322513","doi":"https://doi.org/10.1145/3485447.3512188"},"language":"en","primary_location":{"id":"doi:10.1145/3485447.3512188","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512188","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"},"type":"conference-paper","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/A5061198219","display_name":"Suman K. Bera","orcid":"https://orcid.org/0000-0002-5699-2948"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Suman K. Bera","raw_affiliation_strings":["Katana Graph, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Katana Graph, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082853347","display_name":"Syamantak Das","orcid":"https://orcid.org/0000-0002-4393-8678"},"institutions":[{"id":"https://openalex.org/I119939252","display_name":"Indraprastha Institute of Information Technology Delhi","ror":"https://ror.org/03vfp4g33","country_code":"IN","type":"education","lineage":["https://openalex.org/I119939252"]},{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Syamantak Das","raw_affiliation_strings":["IIIT Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIIT Delhi, India","institution_ids":["https://openalex.org/I119939252","https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112842550","display_name":"Sainyam Galhotra","orcid":null},"institutions":[{"id":"https://openalex.org/I40347166","display_name":"University of Chicago","ror":"https://ror.org/024mw5h28","country_code":"US","type":"education","lineage":["https://openalex.org/I40347166"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sainyam Galhotra","raw_affiliation_strings":["University of Chicago, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chicago, USA","institution_ids":["https://openalex.org/I40347166"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019639292","display_name":"Sagar Kale","orcid":"https://orcid.org/0000-0001-7765-4860"},"institutions":[{"id":"https://openalex.org/I129774422","display_name":"University of Vienna","ror":"https://ror.org/03prydq77","country_code":"AT","type":"education","lineage":["https://openalex.org/I129774422"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Sagar Sudhir Kale","raw_affiliation_strings":["University of Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Vienna, Austria","institution_ids":["https://openalex.org/I129774422"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1414","last_page":"1422"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9986000061035156,"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/T10764","display_name":"Privacy-Preserving Technologies in Data","score":0.9986000061035156,"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9674999713897705,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.8211174011230469},{"id":"https://openalex.org/keywords/automatic-summarization","display_name":"Automatic summarization","score":0.8111436367034912},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.748023271560669},{"id":"https://openalex.org/keywords/center","display_name":"Center (category theory)","score":0.5633634328842163},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5410538911819458},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5383016467094421},{"id":"https://openalex.org/keywords/radius","display_name":"RADIUS","score":0.5001657009124756},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4917588531970978},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4378967583179474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23558345437049866},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13817763328552246},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.10072138905525208}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8211174011230469},{"id":"https://openalex.org/C170858558","wikidata":"https://www.wikidata.org/wiki/Q1394144","display_name":"Automatic summarization","level":2,"score":0.8111436367034912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.748023271560669},{"id":"https://openalex.org/C2779463800","wikidata":"https://www.wikidata.org/wiki/Q5062222","display_name":"Center (category theory)","level":2,"score":0.5633634328842163},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5410538911819458},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5383016467094421},{"id":"https://openalex.org/C178635117","wikidata":"https://www.wikidata.org/wiki/Q747499","display_name":"RADIUS","level":2,"score":0.5001657009124756},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4917588531970978},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4378967583179474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23558345437049866},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13817763328552246},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.10072138905525208},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C8010536","wikidata":"https://www.wikidata.org/wiki/Q160398","display_name":"Crystallography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"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:10.1145/3485447.3512188","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3485447.3512188","pdf_url":null,"source":{"id":"https://openalex.org/S4363608783","display_name":"Proceedings of the ACM Web Conference 2022","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the ACM Web Conference 2022","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/5","score":0.7599999904632568,"display_name":"Gender equality"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1973264045","https://openalex.org/W2018977290","https://openalex.org/W2031184399","https://openalex.org/W2034616054","https://openalex.org/W2070412788","https://openalex.org/W2161392727","https://openalex.org/W2189949549","https://openalex.org/W2353534269","https://openalex.org/W2588799281","https://openalex.org/W2765269579","https://openalex.org/W2947657760","https://openalex.org/W2963388857","https://openalex.org/W2991044292","https://openalex.org/W4214560154","https://openalex.org/W4300033161"],"related_works":["https://openalex.org/W2366403280","https://openalex.org/W1495108544","https://openalex.org/W2091301346","https://openalex.org/W3148229873","https://openalex.org/W4389760904","https://openalex.org/W2150160875","https://openalex.org/W4242223894","https://openalex.org/W4306886878","https://openalex.org/W2973759123","https://openalex.org/W1517524280"],"abstract_inverted_index":{"Center-based":[0],"clustering":[1,28],"techniques":[2],"are":[3,33],"fundamental":[4],"to":[5,48,66],"many":[6],"real-world":[7],"applications":[8],"such":[9,58,70],"as":[10,59],"data":[11],"summarization":[12],"and":[13,80],"social":[14],"network":[15],"analysis.":[16],"In":[17],"this":[18],"work,":[19],"we":[20],"study":[21],"the":[22,81],"problem":[23],"of":[24,41,84],"fairness":[25],"aware":[26],"k-center":[27],"over":[29],"large":[30],"datasets.":[31],"We":[32],"given":[34],"an":[35],"input":[36],"dataset":[37],"comprising":[38],"a":[39,49,55],"set":[40],"n":[42],"points,":[43],"where":[44],"each":[45],"point":[46],"belongs":[47],"specific":[50],"demographic":[51],"group":[52],"characterized":[53],"by":[54],"protected":[56],"attribute,":[57],"race":[60],"or":[61],"gender.":[62],"The":[63],"goal":[64],"is":[65,87],"identify":[67],"k":[68],"clusters":[69,73,86],"that":[71],"all":[72,78],"have":[74],"considerable":[75],"representation":[76],"from":[77],"groups":[79],"maximum":[82],"radius":[83],"these":[85],"minimized.":[88]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}