The shear volume of the results in traditional support based frequent sequential pattern mining methods has led to increasing interest in new intelligent mining methods to find mo...
This paper presents a novel and notable swarm approach to evolve an optimal set of weights and architecture of a neural network for classification in data mining. In a distributed ...
In this work we focus on the problem of frequent itemset mining on large, out-of-core data sets. After presenting a characterization of existing out-of-core frequent itemset minin...
Mining frequent itemsets from transactional datasets is a well known problem with good algorithmic solutions. In the case of uncertain data, however, several new techniques have be...
We present a rigorous framework, based on optimization, for evaluating data mining operations such as associations and clustering, in terms of their utility in decisionmaking. Thi...
Jon M. Kleinberg, Christos H. Papadimitriou, Prabh...