Mining frequent itemsets from data streams has proved to be very difficult because of computational complexity and the need for real-time response. In this paper, we introduce a no...
Finding and removingoutliers is an important problem in data mining. Errors in large databases can be extremely common,so an important property of a data mining algorithm is robus...
In spatial data mining, a common task is the discovery of spatial association rules from spatial databases. We propose a distributed system, named ARES that takes advantage of the ...
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
This paper presents an approach on mining most specific workflow models from event-based data. The approach is embedded in the context of data mining and knowledge discovery in dat...