Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...
iLTL is a probabilistic temporal logic that can specify properties of multiple discrete time Markov chains (DTMCs). In this paper, we describe two related tools: MarkovEstimator a...
We present a new algorithm for mining maximal frequent itemsets from a transactional database. Our algorithm is especially efficient when the itemsets in the database are very lon...
We present an interactive discovery support system, which for a given starting concept of interest, discovers new, potentially meaningful relations with other concepts that have no...
A relevance filter is proposed which removes features based on the mutual information between class labels and features. It is proven that both feature independence and class condi...