Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61892
Title: Experience-Oriented Knowledge Management for Internet of Things
Contributor(s): Zhang, Haoxi (author); Sanin, Cesar  (author)orcid ; Szczerbicki, Edward (author)
Publication Date: 2016-02-27
DOI: 10.1007/978-3-319-31277-4_20
Handle Link: https://hdl.handle.net/1959.11/61892
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.

Publication Type: Book Chapter
Source of Publication: Recent Developments in Intelligent Information and Database Systems, p. 235-242
Publisher: Springer, Cham
Place of Publication: Germany
ISBN: 9783319312774
9783319810041
9783319312767
Fields of Research (FoR) 2020: 4602 Artificial intelligence
HERDC Category Description: B1 Chapter in a Scholarly Book
Series Name: Studies in Computational Intelligence
Series Number : 642
Editor: Editor(s): Dariusz Król, Lech Madeyski and Ngoc Thanh Nguyen
Appears in Collections:Book Chapter
School of Science and Technology

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