Abstract. Deploying process-driven information systems is a time-consuming and error-prone task. Process mining attempts to improve this by automatically generating a process model...
Abstract In this paper we propose a novel parallel algorithm for frequent itemset mining. The algorithm is based on the filter-stream programming model, in which the frequent item...
Adriano Veloso, Wagner Meira Jr., Renato Ferreira,...
In this paper, we propose a new framework for mining frequent patterns from large transactional databases. The core of the framework is of a novel coded prefix-path tree with two...
During social interactions in a community, there are often sub-communities that behave in opposite manner. These antagonistic sub-communities could represent groups of people with ...
Data mining is a new, important and fast growing database application. Outlier (exception) detection is one kind of data mining, which can be applied in a variety of areas like mon...