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Experience-Oriented Knowledge Management for Internet of Things

Haoxi Zhang, Cesar Sanin, Edward Szczerbicki

Research output: Chapter in Book/Report/Conference proceedingChapterResearchpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationRecent Developments in Intelligent Information and Database Systems
EditorsDariusz Król, Lech Madeyski, Ngoc Thanh Nguyen
Place of PublicationGermany
PublisherSpringer, Cham
Pages235-242
ISBN (Print)9783319312774, 9783319810041, 9783319312767
DOIs
Publication statusPublished - 27 Feb 2016

Publication series

NameStudies in Computational Intelligence
Number642
ISSN (Print)1860-949X
ISSN (Electronic)1860-9503

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