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
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
Innovations in Big Data Mining and Embedded Knowledge
276
Innovations in Big Data Mining and Embedded Knowledge
276Paperback(1st ed. 2019)
Product Details
| ISBN-13: | 9783030159412 |
|---|---|
| Publisher: | Springer International Publishing |
| Publication date: | 08/14/2020 |
| Series: | Intelligent Systems Reference Library , #159 |
| Edition description: | 1st ed. 2019 |
| Pages: | 276 |
| Product dimensions: | 6.10(w) x 9.25(h) x (d) |