We consider a model in which background knowledge on a given domain of interest is available in terms of a Bayesian network, in addition to a large database. The mining problem is...
In this paper, we propose a new feature extraction method, which is robust against rotation and histogram equalization for texture classification. To this end, we introduce the co...
Abstract. Data mining algorithms are often embedded in more complex systems, serving as the provider of data for internal decision making within these systems. In this paper we add...
In this paper, we propose a new framework for mining frequent patterns from large transactional databases. The core of the framework is of a novel coded prefix-path tree with two...
Relational databases hold a vast quantity of information and making them accessible to the web is an big challenge. There is a need to make these databases accessible with as litt...