{"id":"https://openalex.org/W4407946322","doi":"https://doi.org/10.1109/tai.2025.3545800","title":"Ensuring Fairness in Spectral Clustering via Disparate Impact-Based Graph Construction","display_name":"Ensuring Fairness in Spectral Clustering via Disparate Impact-Based Graph Construction","publication_year":2025,"publication_date":"2025-02-25","ids":{"openalex":"https://openalex.org/W4407946322","doi":"https://doi.org/10.1109/tai.2025.3545800"},"language":"en","primary_location":{"id":"doi:10.1109/tai.2025.3545800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2025.3545800","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Artificial Intelligence","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/A5055768801","display_name":"Adithya K Moorthy","orcid":"https://orcid.org/0009-0004-2871-8548"},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Adithya K. Moorthy","raw_affiliation_strings":["Indian Institute of Technology, Guwahati, India"],"raw_orcid":"https://orcid.org/0009-0004-2871-8548","affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Guwahati, India","institution_ids":["https://openalex.org/I1317621060"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106450164","display_name":"V. Vijaya Saradhi","orcid":null},"institutions":[{"id":"https://openalex.org/I1317621060","display_name":"Indian Institute of Technology Guwahati","ror":"https://ror.org/0022nd079","country_code":"IN","type":"education","lineage":["https://openalex.org/I1317621060"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"V. Vijaya Saradhi","raw_affiliation_strings":["Indian Institute of Technology, Guwahati, India","Indian Institute of Technology, Guwahati, Assam, India"],"raw_orcid":"https://orcid.org/0000-0002-7856-5322","affiliations":[{"raw_affiliation_string":"Indian Institute of Technology, Guwahati, India","institution_ids":["https://openalex.org/I1317621060"]},{"raw_affiliation_string":"Indian Institute of Technology, Guwahati, Assam, India","institution_ids":["https://openalex.org/I1317621060"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108033355","display_name":"Bhanu Prasad","orcid":"https://orcid.org/0000-0002-3585-655X"},"institutions":[{"id":"https://openalex.org/I8248082","display_name":"Florida Agricultural and Mechanical University","ror":"https://ror.org/00c4wc133","country_code":"US","type":"education","lineage":["https://openalex.org/I8248082"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bhanu Prasad","raw_affiliation_strings":["Florida A&#x0026;M University, Tallahassee, FL, USA"],"raw_orcid":"https://orcid.org/0000-0002-3585-655X","affiliations":[{"raw_affiliation_string":"Florida A&#x0026;M University, Tallahassee, FL, USA","institution_ids":["https://openalex.org/I8248082"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"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":0.01319522,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":"8","first_page":"2342","last_page":"2352"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.996999979019165,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.996999979019165,"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/T10057","display_name":"Face and Expression Recognition","score":0.9944999814033508,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9907000064849854,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5856015682220459},{"id":"https://openalex.org/keywords/spectral-clustering","display_name":"Spectral clustering","score":0.5554806590080261},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.523007333278656},{"id":"https://openalex.org/keywords/disparate-impact","display_name":"Disparate impact","score":0.5062035918235779},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4577343761920929},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.3376997113227844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.23485863208770752},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.17355912923812866}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5856015682220459},{"id":"https://openalex.org/C105611402","wikidata":"https://www.wikidata.org/wiki/Q2976589","display_name":"Spectral clustering","level":3,"score":0.5554806590080261},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.523007333278656},{"id":"https://openalex.org/C2776889015","wikidata":"https://www.wikidata.org/wiki/Q5282532","display_name":"Disparate impact","level":3,"score":0.5062035918235779},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4577343761920929},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3376997113227844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.23485863208770752},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.17355912923812866},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C2778272461","wikidata":"https://www.wikidata.org/wiki/Q190752","display_name":"Supreme court","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tai.2025.3545800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2025.3545800","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["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 Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.5}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1977958056","https://openalex.org/W2014352947","https://openalex.org/W2037444913","https://openalex.org/W2039934205","https://openalex.org/W2053186076","https://openalex.org/W2055588122","https://openalex.org/W2107241511","https://openalex.org/W2121947440","https://openalex.org/W2138388365","https://openalex.org/W2399508263","https://openalex.org/W2617467128","https://openalex.org/W2768467070","https://openalex.org/W2788334832","https://openalex.org/W2904965361","https://openalex.org/W2951747536","https://openalex.org/W2964012239","https://openalex.org/W3021306346","https://openalex.org/W3033293774","https://openalex.org/W3103976293","https://openalex.org/W3136737181","https://openalex.org/W3157999218","https://openalex.org/W4206323856","https://openalex.org/W4238964348","https://openalex.org/W4296186062","https://openalex.org/W4367047017","https://openalex.org/W4385223560","https://openalex.org/W4400761858","https://openalex.org/W4403390515","https://openalex.org/W6677742080","https://openalex.org/W6689213722","https://openalex.org/W6743933341","https://openalex.org/W6746072455","https://openalex.org/W6749201299","https://openalex.org/W6757907451","https://openalex.org/W6758443788","https://openalex.org/W6763290930","https://openalex.org/W6773831323","https://openalex.org/W6779166545","https://openalex.org/W6779682176","https://openalex.org/W6846237036","https://openalex.org/W6907693833","https://openalex.org/W6945341957","https://openalex.org/W7034449035"],"related_works":["https://openalex.org/W2463037423","https://openalex.org/W2168256321","https://openalex.org/W2165870496","https://openalex.org/W104574757","https://openalex.org/W3122603221","https://openalex.org/W1501690958","https://openalex.org/W78752474","https://openalex.org/W3203475907","https://openalex.org/W2599908313","https://openalex.org/W1482912984"],"abstract_inverted_index":{"Spectral":[0],"clustering":[1,25,122],"algorithms":[2],"rely":[3],"on":[4,11,28],"graphs":[5,41],"where":[6],"edges":[7],"are":[8],"defined":[9],"based":[10],"the":[12,15,30,51,76,88,114,140,156],"similarity":[13],"between":[14],"vertices":[16],"(data":[17],"points).":[18],"The":[19,124],"effectiveness":[20],"and":[21,119,155],"fairness":[22,55,72,136,154],"of":[23,53,91,158],"spectral":[24,121,134],"depend":[26],"significantly":[27],"how":[29],"graph":[31,36,65,93,116,132],"is":[32,137],"constructed.":[33],"While":[34],"automated":[35,92],"construction":[37,66,94,117],"methods,":[38],"which":[39],"learn":[40],"from":[42],"real-valued":[43],"vector":[44],"datasets,":[45],"have":[46],"demonstrated":[47],"strong":[48],"performance":[49],"in":[50,100,139,152],"quality":[52,157],"clustering,":[54,135],"concerns":[56],"still":[57],"remain.":[58],"In":[59],"this":[60],"work,":[61],"we":[62],"introduce":[63],"a":[64,70,82,101,130],"method":[67,112,148],"that":[68,146],"incorporates":[69],"new":[71],"definition\u2014Edge":[73],"Disparate":[74],"Impact\u2014into":[75],"edge":[77],"relationships,":[78],"aiming":[79],"to":[80,95,109],"produce":[81],"fair":[83,120,131],"graph.":[84,104],"This":[85],"approach":[86],"modifies":[87],"optimization":[89],"process":[90],"account":[96],"for":[97,133],"fairness,":[98],"resulting":[99,141],"more":[102],"equitable":[103],"Extensive":[105],"experiments":[106],"were":[107],"conducted":[108],"compare":[110],"our":[111,147],"with":[113],"latest":[115],"techniques":[118],"algorithms.":[123],"results":[125],"prove":[126],"that,":[127],"by":[128],"using":[129],"improved":[138],"clusters.":[142],"We":[143],"also":[144],"demonstrate":[145],"outperforms":[149],"baseline":[150],"approaches":[151],"both":[153],"clustering.":[159]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
