Presentation	2003/9/1 Clustering Orders : About the Optimality of Order Means Toshihiro KAMISHIMA, Jun FUJIKI,
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Abstract(in English)	We propose a method of using clustering techniques to partition a set of orders. We define the term order as a sequence of objects that are sorted according to some property, such as size, preference, or price. These orders are useful for, say, carrying out a sensory survey. We propose a method called the κ-o'means method, which is a modified version of a κ-means method, adjusted to handle orders. In this Paper, we will present experimental results in terms of the optimality of the order means.
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Keyword(in English)	Data Mining / Clustering / Order / Questionnaire Survey / Sensory Survey
Paper #	PRMU2003-83
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Conference Information
Committee	PRMU
Conference Date	2003/9/1(1days)
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Paper Information
Registration To	Pattern Recognition and Media Understanding (PRMU)
Language	JPN
Title (in Japanese)	(See Japanese page)
Sub Title (in Japanese)	(See Japanese page)
Title (in English)	Clustering Orders : About the Optimality of Order Means
Sub Title (in English)
Keyword(1)	Data Mining
Keyword(2)	Clustering
Keyword(3)	Order
Keyword(4)	Questionnaire Survey
Keyword(5)	Sensory Survey
1st Author's Name	Toshihiro KAMISHIMA
1st Author's Affiliation	National Institute of Advanced Industrial Science and Technology (AIST)()
2nd Author's Name	Jun FUJIKI
2nd Author's Affiliation	National Institute of Advanced Industrial Science and Technology (AIST)
Date	2003/9/1
Paper #	PRMU2003-83
Volume (vol)	vol.103
Number (no)	295
Page	pp.pp.-
#Pages	6
Date of Issue