{"id":"https://openalex.org/W1993255768","doi":"https://doi.org/10.1109/fuzz-ieee.2014.6891600","title":"Clustering based outlier detection in fuzzy SVM","display_name":"Clustering based outlier detection in fuzzy SVM","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W1993255768","doi":"https://doi.org/10.1109/fuzz-ieee.2014.6891600","mag":"1993255768"},"language":"en","primary_location":{"id":"doi:10.1109/fuzz-ieee.2014.6891600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2014.6891600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","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/A5071378950","display_name":"Rahul K. Sevakula","orcid":"https://orcid.org/0000-0002-6234-367X"},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Rahul K. Sevakula","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology, Kanpur, India","Department of Electrical Engineering, Indian Institute of Technology-Kanpur, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology, Kanpur, India","institution_ids":["https://openalex.org/I94234084"]},{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology-Kanpur, India","institution_ids":["https://openalex.org/I94234084"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014147535","display_name":"Nishchal K. Verma","orcid":"https://orcid.org/0000-0001-8752-5616"},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Nishchal K. Verma","raw_affiliation_strings":["Department of Electrical Engineering, Indian Institute of Technology, Kanpur, India","Department of Electrical Engineering, Indian Institute of Technology-Kanpur, India"],"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology, Kanpur, India","institution_ids":["https://openalex.org/I94234084"]},{"raw_affiliation_string":"Department of Electrical Engineering, Indian Institute of Technology-Kanpur, India","institution_ids":["https://openalex.org/I94234084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5071378950"],"corresponding_institution_ids":["https://openalex.org/I94234084"],"apc_list":null,"apc_paid":null,"fwci":1.6361,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.86758086,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1172","last_page":"1177"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9988999962806702,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9988999962806702,"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":0.9975000023841858,"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/T10820","display_name":"Fuzzy Logic and Control Systems","score":0.9937999844551086,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7534951567649841},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6663148403167725},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6372338533401489},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.569654643535614},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.554686963558197},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5517565011978149},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5350186824798584},{"id":"https://openalex.org/keywords/fuzzy-logic","display_name":"Fuzzy logic","score":0.5143107175827026},{"id":"https://openalex.org/keywords/fuzzy-clustering","display_name":"Fuzzy clustering","score":0.49097517132759094},{"id":"https://openalex.org/keywords/fuzzy-set","display_name":"Fuzzy set","score":0.47832393646240234},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.45099592208862305},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.441937118768692},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.43688833713531494},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.41404759883880615},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.329532265663147}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7534951567649841},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6663148403167725},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6372338533401489},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.569654643535614},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.554686963558197},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5517565011978149},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5350186824798584},{"id":"https://openalex.org/C58166","wikidata":"https://www.wikidata.org/wiki/Q224821","display_name":"Fuzzy logic","level":2,"score":0.5143107175827026},{"id":"https://openalex.org/C17212007","wikidata":"https://www.wikidata.org/wiki/Q5511111","display_name":"Fuzzy clustering","level":3,"score":0.49097517132759094},{"id":"https://openalex.org/C42011625","wikidata":"https://www.wikidata.org/wiki/Q1055058","display_name":"Fuzzy set","level":3,"score":0.47832393646240234},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.45099592208862305},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.441937118768692},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.43688833713531494},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.41404759883880615},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.329532265663147},{"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fuzz-ieee.2014.6891600","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fuzz-ieee.2014.6891600","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Partnerships for the goals","id":"https://metadata.un.org/sdg/17","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1506588750","https://openalex.org/W1551909886","https://openalex.org/W1673310716","https://openalex.org/W1993615430","https://openalex.org/W2000634992","https://openalex.org/W2113076747","https://openalex.org/W2118978333","https://openalex.org/W2143750468","https://openalex.org/W2147813562","https://openalex.org/W2149298154","https://openalex.org/W2153635508","https://openalex.org/W6630208708","https://openalex.org/W6633119224","https://openalex.org/W6637131181"],"related_works":["https://openalex.org/W2280422768","https://openalex.org/W3143197806","https://openalex.org/W4252555497","https://openalex.org/W3121175838","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729"],"abstract_inverted_index":{"Fuzzy":[0,117],"Support":[1],"Vector":[2],"Machine":[3],"(FSVM)":[4],"has":[5],"become":[6],"a":[7,43,100],"handy":[8],"tool":[9],"for":[10,46,122,135,147],"many":[11],"classification":[12],"problems.":[13],"FSVM":[14,27,136],"provides":[15],"flexibility":[16],"of":[17,26,78,103,131],"incorporating":[18],"membership":[19,34,48,60,88,101,124],"values":[20,35,49,89,125],"to":[21,38,58,74],"individual":[22],"training":[23,40],"samples.":[24,41],"Performance":[25],"largely":[28],"depends":[29],"on":[30,91],"how":[31],"well":[32],"these":[33],"are":[36,56],"assigned":[37,87,99],"the":[39,67,76,108,114,151],"Recently,":[42],"new":[44],"approach":[45,110],"assigning":[47,123],"was":[50],"proposed,":[51],"where":[52],"only":[53],"possible":[54,79,83],"outliers":[55,80,84],"allowed":[57],"have":[59,139],"value":[61,102],"lower":[62],"than":[63],"`l'.":[64,104],"For":[65],"doing":[66],"same,":[68],"first":[69],"DBSCAN":[70],"clustering":[71,119],"is":[72],"performed":[73,141],"find":[75],"set":[77],"and":[81,126,149],"such":[82],"were":[85,98],"then":[86],"based":[90,120],"some":[92],"heuristics.":[93],"All":[94],"other":[95],"remaining":[96],"samples":[97],"This":[105],"paper":[106],"extends":[107],"same":[109],"by":[111],"further":[112],"analyzing":[113,150],"algorithm,":[115],"introducing":[116],"C-Means":[118],"heuristic":[121],"also":[127],"comparing":[128,148],"two":[129],"methods":[130],"finding":[132],"optimal":[133],"parameters":[134],"model.":[137],"Experiments":[138],"been":[140],"over":[142],"4":[143],"real":[144],"world":[145],"datasets":[146],"different":[152],"methods.":[153]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
