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Abstract
In this paper, we propose a novel approach for knowledge management in Internet of Things. By utilizing Decisional DNA and deep learning technologies, our approach enables Internet of Things of experiential knowledge discovery, representation, reuse, and sharing among each other. Rather than using traditional machine learning and knowledge discovery methods, this approach focuses on capturing domain’s decisional events via Decisional DNA, and abstracting knowledge through deep learning process based on captured events data. The Decisional DNA is a flexible, domain-independent, and standard experiential knowledge repository solution that allows knowledge to be represented, reused, and easily shared. The main features, architecture, and an initial experiment of this approach are introduced. The presented conceptual approach demonstrates how knowledge can be discovered through its domain’s experiences, and stored and shared as Decisional DNA.
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Authors (3)
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Haoxi Zhang
- Chengdu University Computer Science
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Cesar Sanin
- Newcastle University School of Engineering
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Keywords
Details
- Category:
- Monographic publication
- Type:
- rozdział, artykuł w książce - dziele zbiorowym /podręczniku w języku o zasięgu międzynarodowym
- Title of issue:
- Recent Developments in Intelligent Information and Database Systems strony 235 - 242
- Language:
- English
- Publication year:
- 2016
- Bibliographic description:
- Zhang H., Sanin C., Szczerbicki E.: Experience-Oriented Knowledge Management for Internet of Things// Recent Developments in Intelligent Information and Database Systems/ ed. D. Krol Berlin: Springer, 2016, s.235-242
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/978-3-319-31277-4_20
- Verified by:
- Gdańsk University of Technology
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