Supervised and unsupervised learning methods have traditionally focused on data consisting of independent instances of a single type. However, many real-world domains are best des...
Abstract Clustering text data streams is an important issue in data mining community and has a number of applications such as news group filtering, text crawling, document organiza...
In this paper, a new wavelet-domain codebook design algorithm is proposed for image coding. The method utilizes mean-squared error and variance based selection schemes for good cl...
Momotaz Begum, Nurun Nahar, Kaneez Fatimah, M. K. ...
Clustering is a common methodology for analyzing the gene expression data. In this paper, we present a new clustering algorithm from an information-theoretic point of view. First,...
Traditional similarity or distance measurements usually become meaningless when the dimensions of the datasets increase, which has detrimental effects on clustering performance. I...