Scaling MDS for Preference Data Using Target Configuration
DC Field | Value | Language |
---|---|---|
dc.contributor.author | S.Y.Hwang | - |
dc.contributor.author | S.K.Park | - |
dc.date.available | 2021-02-22T16:18:14Z | - |
dc.date.issued | 2003-06 | - |
dc.identifier.issn | 1598-9402 | - |
dc.identifier.uri | https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/16237 | - |
dc.description.abstract | MDS(multi-dimensional scaling) for preference data is a graphical tool which usually figures out how consumers recognize, evaluate certain products. This article is mainly concerned with an optimal scaling for MDS when target configuration is available. Rotation of axis and SUR(seemingly unrelated regression) methods are employed to get a new configuration which is obtained as close to the target as we can. Methodologies developed here are also illustrated via a real data set. | - |
dc.format.extent | 9 | - |
dc.language | 한국어 | - |
dc.language.iso | KOR | - |
dc.publisher | 한국데이터정보과학회 | - |
dc.title | Scaling MDS for Preference Data Using Target Configuration | - |
dc.type | Article | - |
dc.publisher.location | 대한민국 | - |
dc.identifier.bibliographicCitation | 한국데이터정보과학회지, v.14, no.2, pp 237 - 245 | - |
dc.citation.title | 한국데이터정보과학회지 | - |
dc.citation.volume | 14 | - |
dc.citation.number | 2 | - |
dc.citation.startPage | 237 | - |
dc.citation.endPage | 245 | - |
dc.identifier.kciid | ART000898081 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | kciCandi | - |
dc.identifier.url | https://www.dbpia.co.kr/pdf/pdfView.do?nodeId=NODE07243608&mark=0&bookmarkCnt=0&ipRange=N&accessgl=Y&language=ko_KR | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
Sookmyung Women's University. Cheongpa-ro 47-gil 100 (Cheongpa-dong 2ga), Yongsan-gu, Seoul, 04310, Korea02-710-9127
Copyright©Sookmyung Women's University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.