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Abstract
In this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing, improving, and sharing knowledge among machines and computing devices. It is constructed in a similar fashion of how DNA formed: built up by four essential elements.
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Authors (3)
-
Haoxi Zhang
- Chengdu University, China Computer Science
-
Cesar Sanin
- University of Newcastle, Australia School of Engineering
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- Publication version
- Accepted or Published Version
- DOI:
- Digital Object Identifier (open in new tab) 10.3233/JIFS-169151
- License
- Copyright (2017 IOS Press)
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- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
no. 32,
pages 1575 - 1584,
ISSN: 1064-1246 - Language:
- English
- Publication year:
- 2017
- Bibliographic description:
- Zhang H., Sanin C., Szczerbicki E.: Towards neural knowledge DNA// JOURNAL OF INTELLIGENT & FUZZY SYSTEMS. -Vol. 32, iss. 2 (2017), s.1575-1584
- DOI:
- Digital Object Identifier (open in new tab) 10.3233/jifs-169151
- Verified by:
- Gdańsk University of Technology
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