摘要: In this paper we describe our approaches to data mining in temporal databases by introducing Easy Miner, system developed at UMIST. Miner integrates machine learning methodologies with database technologies and efficiently effectively extract interesting rules from data. The discovery components of relevance analysis, classification association finder are presented the algorithms behind each component. We also show effectiveness these experimental results obtained applying techniques time-oriented medical