{"id":"https://openalex.org/W1527510648","doi":"https://doi.org/10.1109/ijcnn.2003.1223485","title":"Support vector visualization and clustering using self-organizing map and vector one-class classification","display_name":"Support vector visualization and clustering using self-organizing map and vector one-class classification","publication_year":2004,"publication_date":"2004-03-02","ids":{"openalex":"https://openalex.org/W1527510648","doi":"https://doi.org/10.1109/ijcnn.2003.1223485","mag":"1527510648"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2003.1223485","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2003.1223485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","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/A5101739082","display_name":"Sitao Wu","orcid":"https://orcid.org/0000-0002-4740-8885"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":true,"raw_author_name":"Sitao Wu","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China","Dept. of Electron. Eng., Hong Kong City Univ., China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Dept. of Electron. Eng., Hong Kong City Univ., China","institution_ids":["https://openalex.org/I168719708"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050716572","display_name":"Tommy W. S. Chow","orcid":"https://orcid.org/0000-0001-7051-0434"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"T.W.S. Chow","raw_affiliation_strings":["Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China","Dept. of Electron. Eng., Hong Kong City Univ., China"],"affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Dept. of Electron. Eng., Hong Kong City Univ., China","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101739082"],"corresponding_institution_ids":["https://openalex.org/I168719708"],"apc_list":null,"apc_paid":null,"fwci":1.3491,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.83652484,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"803","last_page":"808"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9918000102043152,"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/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9918000102043152,"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":0.991100013256073,"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":0.987500011920929,"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":0.8382093906402588},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7247726917266846},{"id":"https://openalex.org/keywords/self-organizing-map","display_name":"Self-organizing map","score":0.6790762543678284},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6530210375785828},{"id":"https://openalex.org/keywords/clustering-high-dimensional-data","display_name":"Clustering high-dimensional data","score":0.5323097705841064},{"id":"https://openalex.org/keywords/correlation-clustering","display_name":"Correlation clustering","score":0.5314551591873169},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5134921669960022},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.490861713886261},{"id":"https://openalex.org/keywords/cure-data-clustering-algorithm","display_name":"CURE data clustering algorithm","score":0.46143412590026855},{"id":"https://openalex.org/keywords/single-linkage-clustering","display_name":"Single-linkage clustering","score":0.44226595759391785},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4331055283546448}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.8382093906402588},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7247726917266846},{"id":"https://openalex.org/C111168008","wikidata":"https://www.wikidata.org/wiki/Q1136838","display_name":"Self-organizing map","level":3,"score":0.6790762543678284},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6530210375785828},{"id":"https://openalex.org/C184509293","wikidata":"https://www.wikidata.org/wiki/Q5136711","display_name":"Clustering high-dimensional data","level":3,"score":0.5323097705841064},{"id":"https://openalex.org/C94641424","wikidata":"https://www.wikidata.org/wiki/Q5172845","display_name":"Correlation clustering","level":3,"score":0.5314551591873169},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5134921669960022},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.490861713886261},{"id":"https://openalex.org/C33704608","wikidata":"https://www.wikidata.org/wiki/Q5014717","display_name":"CURE data clustering algorithm","level":4,"score":0.46143412590026855},{"id":"https://openalex.org/C22648726","wikidata":"https://www.wikidata.org/wiki/Q7523744","display_name":"Single-linkage clustering","level":5,"score":0.44226595759391785},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4331055283546448}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2003.1223485","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2003.1223485","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Joint Conference on Neural Networks, 2003.","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W65738273","https://openalex.org/W1656697623","https://openalex.org/W1943383135","https://openalex.org/W1992419399","https://openalex.org/W2001619934","https://openalex.org/W2084812512","https://openalex.org/W2100294832","https://openalex.org/W2125478079","https://openalex.org/W2134312057","https://openalex.org/W2135346934","https://openalex.org/W2140190241","https://openalex.org/W2156909104","https://openalex.org/W2158001550","https://openalex.org/W2319660501","https://openalex.org/W3036846224","https://openalex.org/W3144619878","https://openalex.org/W4237222446","https://openalex.org/W4239875977","https://openalex.org/W6678534278","https://openalex.org/W6779887223"],"related_works":["https://openalex.org/W2111119584","https://openalex.org/W3186815950","https://openalex.org/W2389934482","https://openalex.org/W2590117803","https://openalex.org/W2111827030","https://openalex.org/W2040929534","https://openalex.org/W3168768270","https://openalex.org/W2388628913","https://openalex.org/W2202413591","https://openalex.org/W2393707058"],"abstract_inverted_index":{"In":[0,66],"this":[1],"paper,":[2],"a":[3,85],"new":[4],"algorithm":[5],"of":[6,34,101,149,156],"support":[7,19,32],"vector":[8,20],"visualization":[9,140],"and":[10,18,118,125,141],"clustering":[11,142,158],"(SVVC)":[12],"based":[13],"on":[14,132,144],"self-organizing":[15],"map":[16,82,111],"(SOM)":[17,83],"one-class":[21],"classification":[22],"(SVOCC)":[23],"is":[24,28,39,84,136,151],"presented.":[25],"Original":[26],"SVOCC":[27],"to":[29,59],"identify":[30],"the":[31,43,68,106,133,154],"domain":[33],"input":[35,102],"data.":[36,103],"When":[37],"it":[38,56],"used":[40,61],"for":[41,47],"clustering,":[42],"high":[44,76],"computational":[45,147],"complexity":[46,148],"identifying":[48],"cluster":[49,116,126],"gaps":[50],"between":[51],"any":[52],"pair":[53],"points":[54],"makes":[55],"less":[57,152],"likely":[58],"be":[60,72,122,129],"in":[62,75],"large":[63],"data":[64,93],"sets.":[65],"addition,":[67],"identified":[69,131],"clusters":[70,120],"cannot":[71],"visually":[73,113],"displayed":[74],"dimensions":[77],"larger":[78],"than":[79,138,153],"three.":[80],"Self-organizing":[81],"neural":[86],"network":[87],"approach,":[88],"which":[89,135],"can":[90,112,121,128],"project":[91],"high-dimensional":[92,115],"into":[94],"usually":[95],"2-D":[96],"grid":[97],"while":[98],"preserving":[99],"topology":[100],"By":[104],"using":[105],"proposed":[107],"SVVC":[108,150],"algorithm,":[109],"resulting":[110],"display":[114],"shapes":[117],"corresponding":[119],"found.":[123],"Outliers":[124],"borders":[127],"clearly":[130],"map,":[134],"better":[137],"other":[139],"methods":[143],"SOM.":[145],"The":[146],"method":[155],"directly":[157],"by":[159],"SVOCC.":[160]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
