Author(s)

Xuemei Shi, Man Chung Chan & Deyi Li

Abstract

Knowledge discovery in databases (KDD) was defined as the non-trivial process of identifying valid, potentially useful and ultimately understandable patterns in data [1]. Knowledge discovery is considered as the overall process of discovering while data mining refers to the applications of algorithms for extracting patterns from data. In this paper, a prototype of a KDD system, refer to as the Knowledge Explorer (KE), has been developed. KE is an interactive and task-driven knowledge discovery system. It has a friendly human-oriented interface and some powerful mining tools. The basic process of discovering and the logical scheme of KE are introduced. Five components of KE, including the database, the domain knowledge hierarchies, the discovery task editor,

Keywords