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SmartShadow-K: an practical knowledge network for joint context inference in everyday life

Published: 05 September 2012 Publication History

Abstract

Smart environments require to percept conditions of people. Current context-aware systems mainly model limited user situations, which constrains their coverage and effect in real world usage. This paper proposes an encyclopedic knowledge network to enable practical context inference in our daily life by: 1) expressing essential semantics of contextual concepts and relations into a well-informed relational network, and 2) exploiting relational semantics to infer various contexts simultaneously. The performance of the approach is validated in real challenging problems and compared with inference of human being.

References

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G.Pan, Y. Xu, Z. Wu, et al, TaskShadow: Toward Seamless Task Migration across Smart Environments, IEEE Intelligent Systems, 26(3): 50--57,2011.
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Ramos, C., Augusto, J. C., and Shapiro, D. Ambient Intelligence---the Next Step for Artificial Intelligence. IEEE Intelligent Systems, 23(2): 15--18,2008.
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Bettinia, C., Brdiczkab, O., Henricksenc, K., et al, A survey of context modeling and reasoning techniques. Pervasive and Mobile Computing, 6(2):161--180,2010.
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Anderson, J. R. A spreading activation theory of memory. Journal of Verb. Learn. & Verb. Behav., 22(3):261--295, 1983.
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Neville, J., Jensen, D., Chickering, M. Relational dependency networks. JMLR, 8: 653--692,2007.
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Espinosa, J., Lieberman, H. EventNet: Inferring Temporal Relations between Commonsense Events. MICAI 2005, 14--18.
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G.Pan, J. Wu, D. Zhang, Z. Wu, GeeAir: a universal multimodal remote control device for home appliances, PUC, 14(8), 2010.

Cited By

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  • (2022)Answering medical questions in Chinese using automatically mined knowledge and deep neural networks: an end-to-end solutionBMC Bioinformatics10.1186/s12859-022-04658-223:1Online publication date: 15-Apr-2022

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  1. SmartShadow-K: an practical knowledge network for joint context inference in everyday life

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    cover image ACM Conferences
    UbiComp '12: Proceedings of the 2012 ACM Conference on Ubiquitous Computing
    September 2012
    1268 pages
    ISBN:9781450312240
    DOI:10.1145/2370216
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 05 September 2012

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    Author Tags

    1. context-awareness
    2. inference
    3. knowledge network

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    Ubicomp '12
    Ubicomp '12: The 2012 ACM Conference on Ubiquitous Computing
    September 5 - 8, 2012
    Pennsylvania, Pittsburgh

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    UbiComp '12 Paper Acceptance Rate 58 of 301 submissions, 19%;
    Overall Acceptance Rate 764 of 2,912 submissions, 26%

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    • (2022)Answering medical questions in Chinese using automatically mined knowledge and deep neural networks: an end-to-end solutionBMC Bioinformatics10.1186/s12859-022-04658-223:1Online publication date: 15-Apr-2022

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