Statistical machine learning techniques for data classification usually assume that all entities are i.i.d. (independent and identically distributed). However, real-world entities...
With the growing volumes of data, exploring the relationships within the huge amounts of data is difficult. Information visualization uses the human perception system to assist use...
We present a novel sequential clustering algorithm which is motivated by the Information Bottleneck (IB) method. In contrast to the agglomerative IB algorithm, the new sequential ...
UDDI is not suitable for handling semantic markups for Web services due to its flat data model and limited search capabilities. In this paper, we introduce an approach to allow for...
Large and complex computer based systems are the result of an evolution process which may take many years. Heterogeneity is an important characteristic of such systems: During the...