{"id":"https://openalex.org/W2000277463","doi":"https://doi.org/10.1504/ijbidm.2005.007318","title":"Support vector machines based on K-means clustering for real-time business intelligence systems","display_name":"Support vector machines based on K-means clustering for real-time business intelligence systems","publication_year":2005,"publication_date":"2005-01-01","ids":{"openalex":"https://openalex.org/W2000277463","doi":"https://doi.org/10.1504/ijbidm.2005.007318","mag":"2000277463"},"language":"en","primary_location":{"id":"doi:10.1504/ijbidm.2005.007318","doi":"https://doi.org/10.1504/ijbidm.2005.007318","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijbidm.2005.007318","pdf_url":null,"source":{"id":"https://openalex.org/S47982532","display_name":"International Journal of Business Intelligence and Data Mining","issn_l":"1743-8187","issn":["1743-8187","1743-8195"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","poland-40","russia-white-list-3","vabb-shw"],"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Business Intelligence and Data Mining","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"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/A5100365369","display_name":"Jiaqi Wang","orcid":"https://orcid.org/0000-0002-8523-3975","observed_orcids":["https://orcid.org/0000-0002-8523-3975","https://orcid.org/0000-0002-7861-7727","https://orcid.org/0009-0000-7018-3613","https://orcid.org/0009-0003-1763-3875","https://orcid.org/0009-0009-2886-1981"]},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Jiaqi Wang","raw_affiliation_strings":["Faculty of Information Technology, University of Technology, Sydney, P.O. Box 123, Broadway, NSW, 2007, Australia.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, University of Technology, Sydney, P.O. Box 123, Broadway, NSW, 2007, Australia.#TAB#","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080738591","display_name":"Xindong Wu","orcid":"https://orcid.org/0000-0003-2396-1704","observed_orcids":["https://orcid.org/0000-0003-2396-1704"]},"institutions":[{"id":"https://openalex.org/I111236770","display_name":"University of Vermont","ror":"https://ror.org/0155zta11","country_code":"US","type":"education","lineage":["https://openalex.org/I111236770"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xindong Wu","raw_affiliation_strings":["Department of Computer, University of Vermont, 33 Colchester Avenue/351 Votey Building, Burlington, VT 05405, USA.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer, University of Vermont, 33 Colchester Avenue/351 Votey Building, Burlington, VT 05405, USA.#TAB#","institution_ids":["https://openalex.org/I111236770"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100438525","display_name":"Chengqi Zhang B","orcid":"https://orcid.org/0000-0001-5715-7154","observed_orcids":["https://orcid.org/0000-0001-5715-7154","https://orcid.org/0000-0002-9035-4990"]},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Chengqi Zhang","raw_affiliation_strings":["Faculty of Information Technology, University of Technology, Sydney, P.O. Box 123, Broadway, NSW, 2007, Australia.#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Technology, University of Technology, Sydney, P.O. Box 123, Broadway, NSW, 2007, Australia.#TAB#","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.9461,"has_fulltext":false,"cited_by_count":147,"citation_normalized_percentile":{"value":0.97916834,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"biblio":{"volume":"1","issue":"1","first_page":"54","last_page":"54"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.6395999789237976,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T13373","display_name":"Data Mining and Machine Learning Applications","score":0.6395999789237976,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12535","display_name":"Machine Learning and Data Classification","score":0.10949999839067459,"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/T12676","display_name":"Machine Learning and ELM","score":0.07240000367164612,"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/support-vector-machine","display_name":"support vector machine","score":0.9990000128746033},{"id":"https://openalex.org/keywords/k-means-clustering","display_name":"K-means clustering","score":0.9980000257492065},{"id":"https://openalex.org/keywords/support-vector-reduction","display_name":"support vector reduction","score":0.9210000038146973},{"id":"https://openalex.org/keywords/real-time-classification","display_name":"real-time classification","score":0.8399999737739563},{"id":"https://openalex.org/keywords/response-time","display_name":"response time","score":0.6150000095367432},{"id":"https://openalex.org/keywords/network-intrusion-detection","display_name":"network intrusion detection","score":0.9929999709129333},{"id":"https://openalex.org/keywords/business-intelligence","display_name":"business intelligence","score":0.4180000126361847}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9057873487472534},{"id":"https://openalex.org/C2767350","wikidata":"https://www.wikidata.org/wiki/Q6662173","display_name":"Business intelligence","level":2,"score":0.6193004250526428},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5927706360816956},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.48041844367980957},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.402422159910202},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3066402077674866}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1504/ijbidm.2005.007318","doi":"https://doi.org/10.1504/ijbidm.2005.007318","is_oa":false,"landing_page_url":"https://doi.org/10.1504/ijbidm.2005.007318","pdf_url":null,"source":{"id":"https://openalex.org/S47982532","display_name":"International Journal of Business Intelligence and Data Mining","issn_l":"1743-8187","issn":["1743-8187","1743-8195"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","cwts-core","poland-40","russia-white-list-3","vabb-shw"],"host_organization":"https://openalex.org/P4310317825","host_organization_name":"Inderscience Publishers","host_organization_lineage":["https://openalex.org/P4310317825"],"host_organization_lineage_names":["Inderscience Publishers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Business Intelligence and Data Mining","raw_type":"journal-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/4104","doi":null,"is_oa":false,"landing_page_url":"http://hdl.handle.net/10453/4104","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1541935275","https://openalex.org/W2084347746","https://openalex.org/W2087347434","https://openalex.org/W2108728387","https://openalex.org/W2108995755","https://openalex.org/W2109943925","https://openalex.org/W2124351082","https://openalex.org/W2148603752","https://openalex.org/W2149684865","https://openalex.org/W2154579312","https://openalex.org/W2159549127","https://openalex.org/W3017143921"],"related_works":["https://openalex.org/W565209509","https://openalex.org/W2392677017","https://openalex.org/W2130828936","https://openalex.org/W1967880316","https://openalex.org/W7135233062","https://openalex.org/W2127406992","https://openalex.org/W2378155381","https://openalex.org/W91477260","https://openalex.org/W1975216308","https://openalex.org/W7098351614"],"abstract_inverted_index":{"Support":[0],"vector":[1],"machines":[2],"(SVM)":[3],"have":[4],"been":[5],"applied":[6,34],"to":[7,94,105,156],"build":[8],"classifiers,":[9],"which":[10],"can":[11,137],"help":[12],"users":[13],"make":[14],"well-informed":[15],"business":[16,37],"decisions.":[17],"Despite":[18],"their":[19],"high":[20],"generalisation":[21],"accuracy,":[22],"the":[23,53,60,69,82,97,107,111,121,130,134,140],"response":[24,54,141],"time":[25,142],"of":[26,55,62,99,143],"SVM":[27,56,71,87,125],"classifiers":[28,57,144],"is":[29,66],"still":[30],"a":[31,152],"concern":[32],"when":[33],"into":[35],"real-time":[36],"intelligence":[38],"systems,":[39],"such":[40],"as":[41],"stock":[42],"market":[43],"surveillance":[44],"and":[45,88,103,129,150],"network":[46],"intrusion":[47],"detection.":[48],"This":[49,65],"paper":[50],"speeds":[51],"up":[52,139],"by":[58,68,145],"reducing":[59,147],"number":[61,98],"support":[63,148],"vectors.":[64],"done":[67],"K-means":[70,83],"(KMSVM)":[72],"algorithm":[73,80,113,123,136],"proposed":[74],"in":[75,110,116],"this":[76,117],"paper.":[77,118],"The":[78,101],"KMSVM":[79,112,122,135],"combines":[81],"clustering":[84],"technique":[85],"with":[86,124],"requires":[89],"one":[90],"more":[91],"input":[92,108],"parameter":[93],"be":[95],"determined:":[96],"clusters.":[100],"criterion":[102],"strategy":[104],"determine":[106],"parameters":[109],"are":[114],"given":[115],"Experiments":[119],"compare":[120],"on":[126],"real-world":[127],"databases,":[128],"results":[131],"show":[132],"that":[133],"speed":[138],"both":[146],"vectors":[149],"maintaining":[151],"similar":[153],"testing":[154],"accuracy":[155],"SVM.":[157],"Copyright":[158],"\u00a9":[159],"2005":[160],"Inderscience":[161],"Enterprises":[162],"Ltd.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":10},{"year":2017,"cited_by_count":7},{"year":2016,"cited_by_count":14},{"year":2015,"cited_by_count":9},{"year":2014,"cited_by_count":9},{"year":2013,"cited_by_count":12},{"year":2012,"cited_by_count":7}],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2016-06-24T00:00:00"}