Intelligent Systems Reference Library
cover

Innovations in Big Data Mining and Embedded Knowledge

Editors: Esposito, Anna, Esposito, Antonietta M., Jain, Lakhmi C. (Eds.)

  • Includes theoretical foundations, practical applications, and case studies
  • Addresses the usefulness of knowledge discovery through data mining and knowledge embedding through innovative models
  •  Includes contributions from various fields to encourage new directions and to find explanations of why data mining and embedding knowledge can be beneficial to organizations
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  • ISBN 978-3-030-15939-9
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  • ISBN 978-3-030-15938-2
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About this book

This book addresses the usefulness of knowledge discovery through data mining. With this aim, contributors from different fields propose concrete problems and applications showing how data mining and discovering embedded knowledge from raw data can be beneficial to social organizations, domestic spheres, and ICT markets.

Data mining or knowledge discovery in databases (KDD) has received increasing interest due to its focus on transforming large amounts of data into novel, valid, useful, and structured knowledge by detecting concealed patterns and relationships.

The concept of knowledge is broad and speculative and has promoted epistemological debates in western philosophies. The intensified interest in knowledge management and data mining stems from the difficulty in identifying computational models able to approximate human behaviors and abilities in resolving organizational, social, and physical problems. Current ICT interfaces are not yet adequately advanced to support and simulate the abilities of physicians, teachers, assistants or housekeepers in domestic spheres. And unlike in industrial contexts where abilities are routinely applied, the domestic world is continuously changing and unpredictable. There are challenging questions in this field: Can knowledge locked in conventions, rules of conduct, common sense, ethics, emotions, laws, cultures, and experiences be mined from data? Is it acceptable for automatic systems displaying emotional behaviors to govern complex interactions based solely on the mining of large volumes of data?

Discussing multidisciplinary themes, the book proposes computational models able to approximate, to a certain degree, human behaviors and abilities in resolving organizational, social, and physical problems.

The innovations presented are of primary importance for:

a.            The academic research community

b.            The ICT market

c.             Ph.D. students and early stage researchers

d.            Schools, hospitals, rehabilitation and assisted-living centers

e.            Representatives from multimedia industries and standardization bodies

Buy this book

eBook n/a
  • ISBN 978-3-030-15939-9
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover n/a
  • ISBN 978-3-030-15938-2
  • Free shipping for individuals worldwide
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Bibliographic Information

Bibliographic Information
Book Title
Innovations in Big Data Mining and Embedded Knowledge
Editors
  • Anna Esposito
  • Antonietta M. Esposito
  • Lakhmi C. Jain
Series Title
Intelligent Systems Reference Library
Series Volume
159
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-15939-9
DOI
10.1007/978-3-030-15939-9
Hardcover ISBN
978-3-030-15938-2
Series ISSN
1868-4394
Edition Number
1
Number of Pages
XXI, 265
Number of Illustrations
18 b/w illustrations, 39 illustrations in colour
Topics