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Contextual Bandit Learning for Activity-Aware Things-of-Interest Recommendation in an Assisted Living Environment

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Databases Theory and Applications (ADC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12610))

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Abstract

Recommendation systems are crucial for providing services to the elderly with Alzheimer’s disease in IoT-based smart home environments. Therefore, we present a Reminder Care System to help Alzheimer patients live safely and independently in their homes. The proposed recommendation system is formulated based on a contextual bandit approach to tackle dynamicity in human activity patterns for accurate recommendations meeting user needs without their feedback. Our experiment results demonstrate the feasibility and effectiveness of the proposed Reminder Care System in real-world IoT-based smart home applications.

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Authors and Affiliations

  1. The University of New South Wales, Sydney, NSW, 2052, Australia

    May S. Altulayan, Chaoran Huang, Lina Yao & Salil Kanhere

  2. The University of Technology Sydney, Ultimo, NSW, 2007, Australia

    **anzhi Wang

Authors
  1. May S. Altulayan
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  2. Chaoran Huang
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  3. Lina Yao
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  4. **anzhi Wang
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  5. Salil Kanhere
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Corresponding authors

Correspondence to Chaoran Huang , Lina Yao , **anzhi Wang or Salil Kanhere .

Editor information

Editors and Affiliations

  1. University of Auckland, Auckland, New Zealand

    Miao Qiao

  2. University of MĂĽnster, MĂĽnster, Germany

    Gottfried Vossen

  3. The University of Queensland, St. Lucia, QLD, Australia

    Sen Wang

  4. University of Queensland, Brisbane, QLD, Australia

    Lei Li

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Altulayan, M.S., Huang, C., Yao, L., Wang, X., Kanhere, S. (2021). Contextual Bandit Learning for Activity-Aware Things-of-Interest Recommendation in an Assisted Living Environment. In: Qiao, M., Vossen, G., Wang, S., Li, L. (eds) Databases Theory and Applications. ADC 2021. Lecture Notes in Computer Science(), vol 12610. Springer, Cham. https://doi.org/10.1007/978-3-030-69377-0_4

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  • DOI: https://doi.org/10.1007/978-3-030-69377-0_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-69376-3

  • Online ISBN: 978-3-030-69377-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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