Learning Context Awareness Model based on User Feedback for Smart Home Service

Kwon SeongCheol; Seyoung Kim; RYU， KWANG RYEL

doi:https://doi.org/10.9708/jksci.2017.22.07.017

Journal of The Korea Society of Computer and Information

Abbr : JKSCI
2017, 22(7), pp.17-29
DOI :https://doi.org/10.9708/jksci.2017.22.07.017
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science

Kwon SeongCheol ¹ , Seyoung Kim ² , RYU， KWANG RYEL ³

¹ 부산대학교
² 부산대학교
³ 부산대학교

ABSTRACT

IRecently, researches on the recognition of indoor user situations through various sensors in a smart home environment are under way. In this paper, the case study was conducted to determine the operation of the robot vacuum cleaner by inferring the user 's indoor situation through the operation of home appliances, because the indoor situation greatly affects the operation of home appliances. In order to collect learning data for indoor situation awareness model learning, we received feedbacks from user when there was a mistake about the cleaning situation. In this paper, we propose a semi-supervised learning method using user feedback data. When we receive a user feedback, we search for the labels of unlabeled data that most fit the feedbacks collected through genetic algorithm, and use this data to learn the model. In order to verify the performance of the proposed algorithm, we performed a comparison experiments with other learning algorithms in the same environment and confirmed that the performance of the proposed algorithm is better than the other algorithms.
KEYWORDS

Smart home , Situation awareness , Semi-supervised Learning , Genetic Algorithm
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