{"id":"https://openalex.org/W4231089492","doi":"https://doi.org/10.1504/ijaisc.2016.10000220","title":"Exploring different kernel functions for kernel-based clustering","display_name":"Exploring different kernel functions for kernel-based clustering","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W4231089492","doi":"https://doi.org/10.1504/ijaisc.2016.10000220"},"language":"en","primary_location":{"id":"doi:10.1504/ijaisc.2016.10000220","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijaisc.2016.10000220","pdf_url":null,"source":{"id":"https://openalex.org/S16418438","display_name":"International Journal of Artificial Intelligence and Soft Computing","issn_l":"1755-4950","issn":["1755-4950","1755-4969"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Artificial Intelligence and Soft Computing","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/A5043736908","display_name":"Smriti Srivastava","orcid":"https://orcid.org/0000-0001-5678-7058"},"institutions":[{"id":"https://openalex.org/I36090812","display_name":"Netaji Subhas University of Technology","ror":"https://ror.org/01fczmh85","country_code":"IN","type":"education","lineage":["https://openalex.org/I36090812"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Smriti Srivastava","raw_affiliation_strings":["Department of Instrumentation and Control Engineering, Netaji Subhas Institute of Technology, New Delhi, 110078, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Instrumentation and Control Engineering, Netaji Subhas Institute of Technology, New Delhi, 110078, India","institution_ids":["https://openalex.org/I36090812"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019975054","display_name":"Meena Tushir","orcid":"https://orcid.org/0000-0002-8251-8430"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Meena Tushir","raw_affiliation_strings":["Department of Electrical Engineering, Maharaja Surajmal Institute of Technology, New Delhi, 110058, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, Maharaja Surajmal Institute of Technology, New Delhi, 110058, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.30403278,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"5","issue":"3","first_page":"177","last_page":"177"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9873999953269958,"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"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9873999953269958,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9602000117301941,"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/T10320","display_name":"Neural Networks and Applications","score":0.925599992275238,"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/kernel-embedding-of-distributions","display_name":"Kernel embedding of distributions","score":0.8167270421981812},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.7450039982795715},{"id":"https://openalex.org/keywords/variable-kernel-density-estimation","display_name":"Variable kernel density estimation","score":0.7352113127708435},{"id":"https://openalex.org/keywords/radial-basis-function-kernel","display_name":"Radial basis function kernel","score":0.7203302383422852},{"id":"https://openalex.org/keywords/kernel-principal-component-analysis","display_name":"Kernel principal component analysis","score":0.6898596286773682},{"id":"https://openalex.org/keywords/string-kernel","display_name":"String kernel","score":0.6123881936073303},{"id":"https://openalex.org/keywords/kernel-method","display_name":"Kernel method","score":0.5756651163101196},{"id":"https://openalex.org/keywords/polynomial-kernel","display_name":"Polynomial kernel","score":0.5694853663444519},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5530680418014526},{"id":"https://openalex.org/keywords/tree-kernel","display_name":"Tree kernel","score":0.5483208894729614},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.5023529529571533},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.46700891852378845},{"id":"https://openalex.org/keywords/kernel-smoother","display_name":"Kernel smoother","score":0.45113450288772583},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44775882363319397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42421793937683105},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.346794456243515},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.20890960097312927},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.09494739770889282},{"id":"https://openalex.org/keywords/discrete-mathematics","display_name":"Discrete mathematics","score":0.08981403708457947}],"concepts":[{"id":"https://openalex.org/C134517425","wikidata":"https://www.wikidata.org/wiki/Q16000131","display_name":"Kernel embedding of distributions","level":4,"score":0.8167270421981812},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.7450039982795715},{"id":"https://openalex.org/C195699287","wikidata":"https://www.wikidata.org/wiki/Q7915722","display_name":"Variable kernel density estimation","level":4,"score":0.7352113127708435},{"id":"https://openalex.org/C75866337","wikidata":"https://www.wikidata.org/wiki/Q7280263","display_name":"Radial basis function kernel","level":4,"score":0.7203302383422852},{"id":"https://openalex.org/C182335926","wikidata":"https://www.wikidata.org/wiki/Q17093020","display_name":"Kernel principal component analysis","level":4,"score":0.6898596286773682},{"id":"https://openalex.org/C55851704","wikidata":"https://www.wikidata.org/wiki/Q7623983","display_name":"String kernel","level":5,"score":0.6123881936073303},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.5756651163101196},{"id":"https://openalex.org/C160446489","wikidata":"https://www.wikidata.org/wiki/Q7226642","display_name":"Polynomial kernel","level":4,"score":0.5694853663444519},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5530680418014526},{"id":"https://openalex.org/C140417398","wikidata":"https://www.wikidata.org/wiki/Q16933942","display_name":"Tree kernel","level":5,"score":0.5483208894729614},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.5023529529571533},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.46700891852378845},{"id":"https://openalex.org/C27406209","wikidata":"https://www.wikidata.org/wiki/Q6394203","display_name":"Kernel smoother","level":5,"score":0.45113450288772583},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44775882363319397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42421793937683105},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.346794456243515},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.20890960097312927},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.09494739770889282},{"id":"https://openalex.org/C118615104","wikidata":"https://www.wikidata.org/wiki/Q121416","display_name":"Discrete mathematics","level":1,"score":0.08981403708457947},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1504/ijaisc.2016.10000220","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijaisc.2016.10000220","pdf_url":null,"source":{"id":"https://openalex.org/S16418438","display_name":"International Journal of Artificial Intelligence and Soft Computing","issn_l":"1755-4950","issn":["1755-4950","1755-4969"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Artificial Intelligence and Soft Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3013206934","https://openalex.org/W3100948281","https://openalex.org/W4291669689","https://openalex.org/W2130792056","https://openalex.org/W4294351650","https://openalex.org/W1983263273","https://openalex.org/W2974741803","https://openalex.org/W2353199197","https://openalex.org/W2351222813","https://openalex.org/W2371064519"],"abstract_inverted_index":{"Kernel":[0,28],"methods":[1,52,80],"are":[2,30,53,142],"ones":[3],"that,":[4],"by":[5,86],"replacing":[6],"the":[7,61],"inner":[8],"product":[9],"with":[10],"positive":[11,132],"definite":[12,126,133],"function,":[13],"implicitly":[14],"perform":[15],"a":[16,23,105],"non-linear":[17],"mapping":[18,35],"of":[19,66,76,109],"input":[20],"data":[21],"into":[22],"high":[24],"dimensional":[25],"feature":[26],"space.":[27],"functions":[29,42,124,155],"used":[31,143],"to":[32,55,60,97],"make":[33],"this":[34,101],"in":[36,47,58,92],"higher":[37],"dimension":[38],"redundant.":[39],"These":[40],"kernel":[41,67,77,110,117,123,134,154],"play":[43],"an":[44],"important":[45],"role":[46],"classification.":[48],"The":[49,64],"kernel-based":[50],"clustering":[51,79,114],"found":[54,96],"be":[56,98],"superior":[57],"accuracy":[59],"conventional":[62],"ones.":[63],"choice":[65],"function":[68],"is":[69],"neither":[70],"easy":[71],"nor":[72],"trivial.":[73],"Various":[74,136],"types":[75],"based":[78,111],"have":[81,120],"been":[82,95],"studied":[83],"so":[84],"far":[85],"many":[87],"researchers,":[88],"where":[89],"Gaussian":[90,159],"kernel,":[91],"particular,":[93],"has":[94],"useful.":[99],"In":[100],"study,":[102],"we":[103],"present":[104],"comprehensive":[106],"comparative":[107],"analysis":[108],"hybrid":[112],"c-means":[113],"using":[115],"different":[116],"functions.":[118,135],"We":[119],"incorporated":[121],"Mercer":[122],"(positive":[125],"kernels)":[127],"as":[128,130],"well":[129],"conditionally":[131],"synthetic":[137],"datasets":[138,141],"and":[139],"real-life":[140],"for":[144],"analysis.":[145],"Experiments":[146],"results":[147],"show":[148],"that":[149],"there":[150],"exist":[151],"other":[152],"robust":[153],"which":[156],"hold":[157],"like":[158],"kernel.":[160]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}