This book is mainly about an innovative and fundamental method called intelligent knowledge to bridge the gap between data mining and knowledge management, two important fields recognized by the information technology (IT) community and business analytics (BA) community respectively. The book includes definitions of the first-order analytic process, second-order analytic process and intelligent knowledge, which have not formally been addressed by either data mining or knowledge management. Based on these concepts, which are especially important in connection with the current Big Data movement, the book describes a framework of domain-driven intelligent knowledge discovery. To illustrate its technical advantages for large-scale data, the book employs established approaches, such as Multiple Criteria Programming, Support Vector Machine and Decision Tree to identify intelligent knowledge incorporated with human knowledge. The book further shows its applicability by means of real-life data analyses in the contexts of internet business and traditional Chinese medicines.

A valuable resource for researchers who want to learn how the results of data mining (hidden patterns) can be used to effectively support decision-making Argues that the human knowledge or preferences of end-users should be combined with the results of data mining to achieve intelligent knowledge, the ultimate goal of data mining Can be used as a textbook for seminars on the interface of data mining and knowledge management fields for both undergraduate and graduate students? Includes supplementary material: sn.pub/extras

Inhalt
Dedication.- Preface.- Data Mining and Knowledge Management.- Foundations of Intelligent Knowledge Management.- Intelligent Knowledge and Habitual Domain.- Domain Driven Intelligent Knowledge Discovery.- Knowledge-Incorporated Multiple Criteria Linear Programming Classifiers.- Knowledge Extraction from Support Vector Machines.- Intelligent Knowledge Acquisition and Application in Customer Churn.- Intelligent Knowledge Management in Expert Mining in Traditional Chinese Medicines.