We propose in this paper an exploratory analysis algorithm for functional data. The method partitions a set of functions into K clusters and represents each cluster by a simple pr...
We develop a method for clustering all types of belief functions, in particular non-consonant belief functions. Such clustering is done when the belief functions concern multiple ...
The co-association (CA) matrix was previously introduced to combine multiple partitions. In this paper, we analyze the CA matrix, and address its difference from the similarity ma...
We propose DHCS, a method of distributed, hierarchical clustering and summarization for online data analysis and mining in sensor networks. Different from the acquisition and aggre...
Evaluating the design of a distributed application is di cult but provides useful information for program development and maintenance. In distributed debugging, for example, proce...