Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
Abstract. Searching objects within a catalog is a problem of increasing importance, as the general public has access to increasing volumes of data. Constraint programming has addre...
To address the limitations of centralized shared storage for cloud computing, we are building Lithium, a distributed storage system designed specifically for virtualization workl...
We propose a method for learning models of people’s motion behaviors in an indoor environment. As people move through their environments, they do not move randomly. Instead, the...
This paper presents a novel approach for knowledge mining from a sparse and repeated measures dataset. Genetic programming based symbolic regression is employed to generate multip...
Katya Vladislavleva, Kalyan Veeramachaneni, Matt B...