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Modelling and Reasoning About Context-Aware Agents over Heterogeneous Knowledge Sources

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Context-Aware Systems and Applications (ICCASA 2016)

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Abstract

This paper presents a conceptual framework and multi-agent model for context-aware decision support in dynamic smart environments based on heterogeneous knowledge sources. The framework relies on distributed ontologies and allows us to model context-aware agents which reason using rules that are derived from ontologies using the notion of multi-context systems. The use of the proposed framework is illustrated using a simple system developed from ontologies considering three different smart environment domains.

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Authors and Affiliations

  1. School of Computer Science, The University of Nottingham, Malaysia Campus, Semenyih, Malaysia

    Hafiz Mahfooz Ul Haque, Abdur Rakib & Ijaz Uddin

Authors
  1. Hafiz Mahfooz Ul Haque
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  2. Abdur Rakib
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  3. Ijaz Uddin
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Corresponding author

Correspondence to Abdur Rakib .

Editor information

Editors and Affiliations

  1. Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam

    Phan Cong Vinh

  2. Thu Dau Mot University, Thu Dau Mot City, Vietnam

    Le Tuan Anh

  3. Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam

    Nguyen Thi Thuy Loan

  4. University of the Thai Chamber of Commerce, Bangkok, Thailand

    Waralak Vongdoiwang Siricharoen

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© 2017 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Mahfooz Ul Haque, H., Rakib, A., Uddin, I. (2017). Modelling and Reasoning About Context-Aware Agents over Heterogeneous Knowledge Sources. In: Cong Vinh, P., Tuan Anh, L., Loan, N., Vongdoiwang Siricharoen, W. (eds) Context-Aware Systems and Applications. ICCASA 2016. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 193. Springer, Cham. https://doi.org/10.1007/978-3-319-56357-2_1

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  • DOI: https://doi.org/10.1007/978-3-319-56357-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56356-5

  • Online ISBN: 978-3-319-56357-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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