Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
This paper introduces the problem of combining multiple partitionings of a set of objects into a single consolidated clustering without accessing the features or algorithms that d...
In this paper, we focus on the ontological concept extraction and evaluation process from HTML documents. In order to improve this process, we propose an unsupervised hierarchical...
Hierarchical metric-space clustering methods have been commonly used to organize proteomes into taxonomies. Consequently, it is often anticipated that hierarchical clustering can ...
Rui Mao, Weijia Xu, Neha Singh, Daniel P. Miranker
We propose a methodology for improved segmentation of images in a Bayesian framework by fusion of color, texture and gradient information. The proposed algorithm is initialized by...