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Fuzzy k-Means Local Centers of the Social Networks
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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | 우원석 | - |
| dc.contributor.author | 허명회 | - |
| dc.date.accessioned | 2021-09-07T03:13:46Z | - |
| dc.date.available | 2021-09-07T03:13:46Z | - |
| dc.date.created | 2021-06-17 | - |
| dc.date.issued | 2012 | - |
| dc.identifier.issn | 2287-7843 | - |
| dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/110383 | - |
| dc.description.abstract | Fuzzy k-means clustering is an attractive alternative to the ordinary k-means clustering in analyzing multivariate data. Fuzzy versions yield more natural output by allowing overlapped k groups. In this study, we modify a fuzzy k-means clustering algorithm to be used for undirected social networks, apply the algorithm to both real and simulated cases, and report the results. | - |
| dc.language | English | - |
| dc.language.iso | en | - |
| dc.publisher | 한국통계학회 | - |
| dc.title | Fuzzy k-Means Local Centers of the Social Networks | - |
| dc.title.alternative | Fuzzy k-Means Local Centers of the Social Networks | - |
| dc.type | Article | - |
| dc.contributor.affiliatedAuthor | 허명회 | - |
| dc.identifier.bibliographicCitation | Communications for Statistical Applications and Methods, v.19, no.2, pp.213 - 217 | - |
| dc.relation.isPartOf | Communications for Statistical Applications and Methods | - |
| dc.citation.title | Communications for Statistical Applications and Methods | - |
| dc.citation.volume | 19 | - |
| dc.citation.number | 2 | - |
| dc.citation.startPage | 213 | - |
| dc.citation.endPage | 217 | - |
| dc.type.rims | ART | - |
| dc.identifier.kciid | ART001645312 | - |
| dc.description.journalClass | 2 | - |
| dc.description.journalRegisteredClass | kci | - |
| dc.subject.keywordAuthor | Fuzzy k-means clustering | - |
| dc.subject.keywordAuthor | social network analysis | - |
| dc.subject.keywordAuthor | local centers | - |
| dc.subject.keywordAuthor | communities. | - |
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