Research Challenges and Solutions for the Knowledge Overload with Data Mining

Abstract

the rapid development of data technology, as exemplified by data mining and Internet growth, creates a large information overload and forthcoming knowledge overload. Data mining discovers a large mount of knowledge, but not all of the knowledge is useful. Meanwhile the useful knowledge will also become un-useful as time goes by. How to manage this kind of knowledge is an urgent problem for data mining applications. A new research field called Intelligent knowledge (IK) is put forward and we try to explain the needs for coining the term as a sub-discipline of BI for systematic studies on knowledge application related theories, as well as the design of Intelligent Knowledge Management Systems (IKMS). Main topics are discussed to demonstrate why we consider IK to be a subject worthy of study and, at the same time, to establish a starting point for the further research.