Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used successfully
Intelligent Knowledge: A Study beyond Data Mining
β Scribed by Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li (auth.)
- Publisher
- Springer-Verlag Berlin Heidelberg
- Year
- 2015
- Tongue
- English
- Leaves
- 160
- Series
- SpringerBriefs in Business
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This book is mainly about an innovative and fundamental method called βintelligent knowledgeβ 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 βfirst-orderβ analytic process, βsecond-orderβ 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.
β¦ Table of Contents
Front Matter....Pages i-xvi
Data Mining and Knowledge Management....Pages 1-11
Foundations of Intelligent Knowledge Management....Pages 13-30
Intelligent Knowledge and Habitual Domain....Pages 31-46
Domain Driven Intelligent Knowledge Discovery....Pages 47-80
Knowledge-incorporated Multiple Criteria Linear Programming Classifiers....Pages 81-100
Knowledge Extraction from Support Vector Machines....Pages 101-111
Intelligent Knowledge Acquisition and Application in Customer Churn....Pages 113-129
Intelligent Knowledge Management in Expert Mining in Traditional Chinese Medicines....Pages 131-139
Back Matter....Pages 141-150
β¦ Subjects
IT in Business; Non-Profit Enterprises/Corporate Social Responsibility; Business Mathematics
π SIMILAR VOLUMES
<p><span>Finding information hidden in data is as theoretically difficult as it is practically important. With the objective of discovering unknown patterns from data, the methodologies of data mining were derived from statistics, machine learning, and artificial intelligence, and are being used suc
Another must by for any level Sas user! Real world examples are the best way to learn. Another great buy!