Intelligent Knowledge: A Study beyond Data Mining

Book Description

This book is mainly about an innovative and fundamental method called “intelligent knowledge” to bridge the gap between and knowledge , two important fields recognized by the technology (IT) community and 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 of domain-driven intelligent knowledge discovery. To illustrate its technical advantages for large-scale data, the book employs established approaches, such as Multiple Criteria , 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 and traditional Chinese medicines.

Table of Contents

Chapter 1 Data Mining and Knowledge Management
Chapter 2 Foundations of Intelligent Knowledge Management
Chapter 3 Intelligent Knowledge and Habitual Domain
Chapter 4 Domain Driven Intelligent Knowledge Discovery
Chapter 5 Knowledge-incorporated Multiple Criteria Linear Programming Classifiers
Chapter 6 Knowledge Extraction from Support Vector Machines
Chapter 7 Intelligent Knowledge Acquisition and Application in Customer Churn
Chapter 8 Intelligent Knowledge Management in Expert Mining in Traditional Chinese Medicines

Book Details

File HostFree Download LinkFormatSize (MB)Upload Date
EU(multi) Click to downloadTrue PDF4.606/29/2015
ZippyShare Click to downloadTrue PDF4.601/07/2016
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