Clustering Orders — About the Optimality of Order Means
Toshihiro Kamishima, Jun Fujiki · 2003
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 k-o'means method, which is a modified version of a k-means method, adjusted to handle orders. In this Paper, we will present experimental results in terms of the optimality of the order means.