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

Yunsick Sung, Haitao Guo, Jong Hyuk Park

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

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.

Original languageEnglish
Pages (from-to)1264-1278
Number of pages15
JournalEnterprise Information Systems
Volume14
Issue number9-10
DOIs
StatePublished - 2020

Keywords

  • activity recognition
  • Cognitive computing
  • probability computing
  • scenario generation

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