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Knowledge Technology = Converting Da...
~
Nakamori, Yoshiteru.
Knowledge Technology = Converting Data and Information into Valuable Ideas /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Knowledge Technology/ by Yoshiteru Nakamori.
Reminder of title:
Converting Data and Information into Valuable Ideas /
Author:
Nakamori, Yoshiteru.
Description:
XI, 120 p. 27 illus., 1 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Knowledge management. -
Online resource:
https://doi.org/10.1007/978-981-16-3253-2
ISBN:
9789811632532
Knowledge Technology = Converting Data and Information into Valuable Ideas /
Nakamori, Yoshiteru.
Knowledge Technology
Converting Data and Information into Valuable Ideas /[electronic resource] :by Yoshiteru Nakamori. - 1st ed. 2021. - XI, 120 p. 27 illus., 1 illus. in color.online resource. - SpringerBriefs in Business,2191-5482. - SpringerBriefs in Business,.
-Preface -- 1. Introduction -- 2. Defining Knowledge Technology -- 3. Integrative Knowledge Technologies -- 4. Converting Data/Knowledge into Information -- 5. Converting Information into Knowledge -- 6. Creating New Ideas from the Knowledge -- 7. Validating the Value of the New Ideas -- 8. Summary and Expectations.
This book reviews creative technologies that underpin the human activities of converting data and information into knowledge, creating new ideas based on that knowledge, and validating those ideas. The book calls such creative technology “knowledge technology” and explores its challenges in the age of big data. Today, artificial intelligence and big data are successfully performing pattern recognition and decision making on behalf of humans, who are incapable of processing large amounts of information instantly and accurately. In using only past data, however, there are limits to future predictions with artificial intelligence and big data. Humans need to take the lead in predicting or creating the future by trying to understand why data emerged. Knowledge technology contributes to that understanding, regardless of the field of origin. As a matter of fact, knowledge technology includes many technologies developed in informatics, management study, and systems science. The desirable features of knowledge technology are the complementary use of rational and intuitive approaches, the integration of results from quantitative and qualitative analyses, and the cooperation between artificial intelligence and humans.
ISBN: 9789811632532
Standard No.: 10.1007/978-981-16-3253-2doiSubjects--Topical Terms:
558406
Knowledge management.
LC Class. No.: HD30.2
Dewey Class. No.: 658.4038
Knowledge Technology = Converting Data and Information into Valuable Ideas /
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-Preface -- 1. Introduction -- 2. Defining Knowledge Technology -- 3. Integrative Knowledge Technologies -- 4. Converting Data/Knowledge into Information -- 5. Converting Information into Knowledge -- 6. Creating New Ideas from the Knowledge -- 7. Validating the Value of the New Ideas -- 8. Summary and Expectations.
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This book reviews creative technologies that underpin the human activities of converting data and information into knowledge, creating new ideas based on that knowledge, and validating those ideas. The book calls such creative technology “knowledge technology” and explores its challenges in the age of big data. Today, artificial intelligence and big data are successfully performing pattern recognition and decision making on behalf of humans, who are incapable of processing large amounts of information instantly and accurately. In using only past data, however, there are limits to future predictions with artificial intelligence and big data. Humans need to take the lead in predicting or creating the future by trying to understand why data emerged. Knowledge technology contributes to that understanding, regardless of the field of origin. As a matter of fact, knowledge technology includes many technologies developed in informatics, management study, and systems science. The desirable features of knowledge technology are the complementary use of rational and intuitive approaches, the integration of results from quantitative and qualitative analyses, and the cooperation between artificial intelligence and humans.
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