Identifying background (context) information in scientific articles can help scholars understand major contributions in their research area more easily. In this paper, we propose ...
Multi-core processors are proliferated across different domains in recent years. In this paper, we study the performance of frequent pattern mining on a modern multi-core machine....
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...
In this article we show that there is a strong connection between decision tree learning and local pattern mining. This connection allows us to solve the computationally hard probl...
Assessing the quality of discovered results is an important open problem in data mining. Such assessment is particularly vital when mining itemsets, since commonly many of the disc...