With the growing use of information technology and the recent advances in web systems, the amount of data available to users has increased exponentially. Thus, there is a critical need to understand the content of the data. As a result, data-mining has become a popular research topic in recent years for the treatment of the “data rich and information poor” syndrome. Currently, application oriented engineers are only concerned with their immediate problems, which results in an ad hoc method of problem solving. Researchers, on the other hand, lack an understanding of the practical issues of data-mining for real-world problems and often concentrate on issues (e.g. incremental performance improvements) that are of no significance to the practitioners.
In this volume, we hope to remedy these problems by (1) presenting a theoretical foundation of data-mining, and (2) providing important new directions for data-mining research. We have invited a set of well respected data mining theoreticians to present their views on the fundamental science of data mining. We have also called on researchers with practical data mining experiences to present new important data-mining topics.
This book is organized into two parts. The first part consists of four chapters presenting the foundations of data mining, which describe the theoretical point of view and the capabilities and limits of current available mining techniques. The second part consists of seven chapters which discuss the new data mining topics.