Supervised approaches to Data Mining are particularly appealing as they allow for the extraction of complex relations from data objects. In order to facilitate their application i...
There has been much recent interest in on-line data mining. Existing mining algorithms designed for stored data are either not applicable or not effective on data streams, where r...
Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...
We present a general Multi-Agent System framework for distributed data mining based on a Peer-toPeer model. The framework adopts message-based asynchronous communication and a dyn...
Abstract. In this paper, we propose a novel mining task: mining frequent superset from the database of itemsets that is useful in bioinformatics, e-learning systems, jobshop schedu...