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Cognitive scenario generation computing in the Internet of things for enterprise information systems

Authors
Sung, YunsickGuo, HaitaoPark, Jong Hyuk
Issue Date
25-Nov-2020
Publisher
TAYLOR & FRANCIS LTD
Keywords
Cognitive computing; activity recognition; probability computing; scenario generation
Citation
ENTERPRISE INFORMATION SYSTEMS, v.14, no.9-10, pp 1264 - 1278
Pages
15
Indexed
SCIE
SCOPUS
Journal Title
ENTERPRISE INFORMATION SYSTEMS
Volume
14
Number
9-10
Start Page
1264
End Page
1278
URI
https://scholarworks.dongguk.edu/handle/sw.dongguk/5893
DOI
10.1080/17517575.2019.1632383
ISSN
1751-7575
1751-7583
Abstract
This paper proposes an enhanced Bayesian probability-based method to generate high-quality scenarios using a small number of collected sensory data. Diverse kinds of new scenarios can be generated inexpensively using the proposed method, and these new scenarios have characteristics similar to the stochastic characteristics of manually collected datasets. The validity of this method was evaluated based on a real dataset. Experiments showed that the factor of the effect was 0.46351, indicating that the proposed method can generate scenarios that are highly consistent with real sensory big data.
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