Biclustering similarity measures for heterogeneous data

Abstract

A similarity measure or distance is a successful key in data mining process and knowledge discovery including biclustering. Many measures are proposed on the specific data type. However, there are different types and characteristics of data in real world. In the paper, we study the performance of a variety of measures on different kind of data and then combine them to evaluate the quality of biclusters.