Innovations in Big Data Mining and Embedded Knowledge

Nonfiction, Computers, Advanced Computing, Artificial Intelligence, Database Management, General Computing
Cover of the book Innovations in Big Data Mining and Embedded Knowledge by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783030159399
Publisher: Springer International Publishing Publication: July 3, 2019
Imprint: Springer Language: English
Author:
ISBN: 9783030159399
Publisher: Springer International Publishing
Publication: July 3, 2019
Imprint: Springer
Language: English

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

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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

More books from Springer International Publishing

Cover of the book Irregular Immigration in Southern Europe by
Cover of the book The Pathobiology of Breast Cancer by
Cover of the book Design of Structural Elements with Tropical Hardwoods by
Cover of the book Fibrous Proteins: Structures and Mechanisms by
Cover of the book Feminist Approaches to Media Theory and Research by
Cover of the book Intelligence Science II by
Cover of the book Intracellular Delivery III by
Cover of the book Integral Methods in Science and Engineering by
Cover of the book Cult Media by
Cover of the book Amorphous Drugs by
Cover of the book Organo-di-Metallic Compounds (or Reagents) by
Cover of the book Cage-based Performance Capture by
Cover of the book Generations of Women Historians by
Cover of the book The Circulation of Anti-Austerity Protest by
Cover of the book Historical Land Use/Land Cover Classification Using Remote Sensing by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy