In this paper, we investigate and utilize the characteristic of the group movement of objects to achieve energy conservation in the inherently resource-constrained wireless object ...
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...
The emerging interests in spatial pattern mining lead to the demand for a flexible spatial pattern mining language, on which easy to use and understand visual pattern language cou...
The support-confidence framework is the most common measure used in itemset mining algorithms, for its antimonotonicity that effectively simplifies the search lattice. This com...
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
In this paper, we propose a new method called Prototype Ranking (PR) designed for the stock selection problem. PR takes into account the huge size of real-world stock data and app...
In this paper we discuss the important practical problem of customer wallet estimation, i.e., estimation of potential spending by customers (rather than their expected spending). ...
Claudia Perlich, Saharon Rosset, Richard D. Lawren...
We describe our project that marries data mining together with Grid computing. Specifically, we focus on one data mining application - the Minnesota Intrusion Detection System (MIN...
Jon B. Weissman, Vipin Kumar, Varun Chandola, Eric...