한국컴퓨터정보학회논문지 (Journal of the Korea Society of Computer and Information)

  • 제22권7호
  • /
  • Pages.17-29
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  • 2017
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  • 1598-849X(pISSN)
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  • 2383-9945(eISSN)
한국컴퓨터정보학회 (Korean Society of Computer Information)
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Learning Context Awareness Model based on User Feedback for Smart Home Service

  • Kwon, Seongcheol (Dept. of Computer Science and Engineering, Pusan National University) ;
  • Kim, Seyoung (Dept. of Computer Science and Engineering, Pusan National University) ;
  • Ryu, Kwang Ryel (Dept. of Computer Science and Engineering, Pusan National University)
  • 투고 : 2017.05.12
  • 심사 : 2017.07.18
  • 발행 : 2017.07.31
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초록

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.

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참고문헌

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