Skip to main content
SpringerLink
Log in
Book cover
  • Book
  • © 2015

Intelligent Knowledge

A Study beyond Data Mining

Authors:

  1. Yong Shi

    1. Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China

    View author publications

    You can also search for this author in PubMed   Google Scholar

  2. Lingling Zhang

    1. School of Management, Univ. of Chinese Academy of Sciences, Beijing, China

    View author publications

    You can also search for this author in PubMed   Google Scholar

  3. Yingjie Tian

    1. Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China

    View author publications

    You can also search for this author in PubMed   Google Scholar

  4. Xingsen Li

    1. School of Management, Ningbo Institute of Technology, Zhejiang University, Ningbo, China

    View author publications

    You can also search for this author in PubMed   Google Scholar

  • 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

Part of the book series: SpringerBriefs in Business (BRIEFSBUSINESS)

Sections

Buy it now

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

This is a preview of subscription content, log in via an institution to check for access.

Table of contents (8 chapters)

  1. Front Matter

    Pages i-xvi
    PDF

  2. Data Mining and Knowledge Management

    • Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li
    Pages 1-11

  3. Foundations of Intelligent Knowledge Management

    • Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li
    Pages 13-30

  4. Intelligent Knowledge and Habitual Domain

    • Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li
    Pages 31-46

  5. Domain Driven Intelligent Knowledge Discovery

    • Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li
    Pages 47-80

  6. Knowledge-incorporated Multiple Criteria Linear Programming Classifiers

    • Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li
    Pages 81-100

  7. Knowledge Extraction from Support Vector Machines

    • Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li
    Pages 101-111

  8. Intelligent Knowledge Acquisition and Application in Customer Churn

    • Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li
    Pages 113-129

  9. Intelligent Knowledge Management in Expert Mining in Traditional Chinese Medicines

    • Yong Shi, Lingling Zhang, Yingjie Tian, Xingsen Li
    Pages 131-139

  10. Back Matter

    Pages 141-150
    PDF
Back to top

About this book

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.
Back to top

Keywords

Back to top

Authors and Affiliations

  • Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing, China

    Yong Shi, Yingjie Tian

  • School of Management, Univ. of Chinese Academy of Sciences, Beijing, China

    Lingling Zhang

  • School of Management, Ningbo Institute of Technology, Zhejiang University, Ningbo, China

    Xingsen Li

Back to top

Bibliographic Information

Back to top

Publish with us

Policies and ethics

Back to top
Access via your institution

Buy it now

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Search

Navigation