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Improved Multidimensional Scaling Techniques Considering Cluster Analysis: Cluster-oriented Scaling

  • Journal of the Korean Society for Information Management
  • Abbr : JKOSIM
  • 2012, 29(2), pp.45~70
  • DOI : 10.3743/KOSIM.2012.29.2.045
  • Publisher : 한국정보관리학회
  • Research Area : Interdisciplinary Studies > Library and Information Science
  • Received : May 7, 2012
  • Accepted : May 30, 2012
  • Published : June 30, 2012

Lee, Jae Yun 1

1경기대학교

Accredited

ABSTRACT

There have been many methods and algorithms proposed for multidimensional scaling to mapping the relationships between data objects into low dimensional space. But traditional techniques, such as PROXSCAL or ALSCAL, were found not effective for visualizing the proximities between objects and the structure of clusters of large data sets have more than 50 objects. The CLUSCAL(CLUster-oriented SCALing) technique introduced in this paper differs from them especially in that it uses cluster structure of input data set. The CLUSCAL procedure was tested and evaluated on two data sets, one is 50 authors co-citation data and the other is 85 words co-occurrence data. The results can be regarded as promising the usefulness of CLUSCAL method especially in identifying clusters on MDS maps.

Citation status

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