This paper presents an unsupervised learning approach to disambiguate various relations between name entities by use of various lexical and syntactic features from the contexts. I...
Jinxiu Chen, Dong-Hong Ji, Chew Lim Tan, Zheng-Yu ...
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 ...
Abstract. Five methods for count data clusterization based on Poisson mixture models are described. Two of them are parametric, the others are semi-parametric. The methods emlploy ...
It is necessary to have the precise definition of available performance of high availability systems that can represent the availability and performability of the systems altogethe...
Traditional clustering is a descriptive task that seeks to identify homogeneous groups of objects based on the values of their attributes. While domain knowledge is always the bes...