DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, J | - |
dc.contributor.author | Lee, D | - |
dc.date.accessioned | 2016-04-01T02:17:03Z | - |
dc.date.available | 2016-04-01T02:17:03Z | - |
dc.date.created | 2009-04-01 | - |
dc.date.issued | 2005-03 | - |
dc.identifier.issn | 0162-8828 | - |
dc.identifier.other | 2005-OAK-0000004799 | - |
dc.identifier.uri | https://oasis.postech.ac.kr/handle/2014.oak/24826 | - |
dc.description.abstract | The support vector clustering (SVC) algorithm is a recently emerged unsupervised learning method inspired by support vector machines. One key step involved in the SVC algorithm is the cluster assignment of each data point. A new cluster labeling method for SVC is developed based on some invariant topological properties of a trained kernel radius function. Benchmark results show that the proposed method outperforms previously reported labeling techniques. | - |
dc.description.statementofresponsibility | X | - |
dc.language | English | - |
dc.publisher | IEEE COMPUTER SOC | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | - |
dc.subject | clustering | - |
dc.subject | unsupervised learning method | - |
dc.subject | support vector machines | - |
dc.title | An improved cluster labeling method for support vector clustering | - |
dc.type | Article | - |
dc.contributor.college | 산업경영공학과 | - |
dc.identifier.doi | 10.1109/TPAMI.2005.47 | - |
dc.author.google | Lee, J | - |
dc.author.google | Lee, D | - |
dc.relation.volume | 27 | - |
dc.relation.issue | 3 | - |
dc.relation.startpage | 461 | - |
dc.relation.lastpage | 464 | - |
dc.contributor.id | 10081901 | - |
dc.relation.journal | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | - |
dc.relation.index | SCI급, SCOPUS 등재논문 | - |
dc.relation.sci | SCI | - |
dc.collections.name | Journal Papers | - |
dc.type.rims | ART | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, v.27, no.3, pp.461 - 464 | - |
dc.identifier.wosid | 000226300200014 | - |
dc.date.tcdate | 2019-02-01 | - |
dc.citation.endPage | 464 | - |
dc.citation.number | 3 | - |
dc.citation.startPage | 461 | - |
dc.citation.title | IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | - |
dc.citation.volume | 27 | - |
dc.contributor.affiliatedAuthor | Lee, J | - |
dc.identifier.scopusid | 2-s2.0-15044345801 | - |
dc.description.journalClass | 1 | - |
dc.description.journalClass | 1 | - |
dc.description.wostc | 190 | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | clustering | - |
dc.subject.keywordAuthor | unsupervised learning method | - |
dc.subject.keywordAuthor | support vector machines | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
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