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Uncertainty in Context-Aware Systems: A Case Study for Intelligent Environments

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Trends and Advances in Information Systems and Technologies (WorldCIST'18 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 745))

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Abstract

Data used be context-aware systems is naturally incomplete and not always reflect real situations. The dynamic nature of intelligent environments leads to the need of analysing and handling uncertain information. Users can change their acting patterns within a short space of time. This paper presents a case study for a better understanding of concepts related to context awareness and the problem of dealing with inaccurate data. Through the analysis of identification of elements that results in the construction of unreliable contexts, it is aimed to identify patterns to minimize incompleteness. Thus, it will be possible to deal with flaws caused by undesired execution of applications.

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Notes

  1. 1.

    https://geist.re/pub:projects:knowme:start.

References

  1. Perera, C., Zaslavsky, A., et al.: Context aware computing for the internet of things: a survey. IEEE Commun. Surv. Tutorials 16(1), 414–454 (2014). https://doi.org/10.1109/SURV.2013.042313.00197

    Article  Google Scholar 

  2. Bobek, S., Nalepa, G.J.: Uncertain context data management in dynamic mobile environments. Future Gener. Comput. Syst. 66, 110–124 (2017)

    Article  Google Scholar 

  3. Alpaydin, E.: Introduction to Machine Learning, 2nd edn. The MIT Press, Cambridge (2010). ISBN 026201243X, 9780262012430

    MATH  Google Scholar 

  4. Buchholz, T., Schiffers, M.: Quality of context: what it is and why we need it. In: Proceedings of the 10th Workshop of the Open View University Association (2003)

    Google Scholar 

  5. Dey, A.K.: Context-aware computing: the CyberDesk project. In: AAAI Spring Symposium on Intelligent Environments, pp. 51–54. AAAI Press, Palo Alto (1998)

    Google Scholar 

  6. Djoudi, B., Bouanaka, C., Zeghib, N.: A formal framework for context-aware systems specification and verification. J. Syst. Softw. 122, 445–462 (2016)

    Article  Google Scholar 

  7. Musumba, G., Nyongesa, H.: Context awareness in mobile computing: a review. Int. J. Mach. Learn. Appl. 2(1) (2013)

    Google Scholar 

  8. Novais, P., Carneiro, D.: The role of non-intrusive approaches in the development of people-aware systems. Prog. AI 5(3), 215–220 (2016). https://doi.org/10.1007/s13748-016-0085-1

    Article  Google Scholar 

  9. Nugroho, L.E.: Context-awareness: connecting computing with its environment. In: 2015 2nd International Conference on Information Technology, Computer, and Electrical Engineering, p. 37 (2015). https://doi.org/10.1109/ICITACEE.2015.7437760

  10. Rukzio, E., Hamard, J., et al.: Visualization of uncertainty in context aware mobile applications. In: 8th Conference on Human-Computer Interaction with Mobile Devices and Services, pp. 247–250 (2006). https://doi.org/10.1145/1152215.1152267

  11. Senge, R., Bösner, S., et al.: Reliable classification: learning classifiers that distinguish aleatoric and epistemic uncertainty. Inf. Sci. 255, 16–29 (2014). https://doi.org/10.1016/j.ins.2013.07.030

    Article  MathSciNet  MATH  Google Scholar 

  12. Sheikh, K., Wegdam, M., van Sinderen, M.J.: Quality-of-context and its use for protecting privacy in context aware systems. J. Softw. 3(3), 83–93 (2008)

    Article  Google Scholar 

  13. Smola, A., Vishwanathan, S.V.N.: Introduction to Machine Learning, 1st edn. Cambridge University Press, Cambridge (2008). ISBN 0521825830

    Google Scholar 

  14. Yaghlane, A.B., Denoeux, T., Mellouli, K.: Uncertainty and intelligent information systems. In: Elicitation of Expert Opinions for Constructing Belief Functions, pp. 75–89. World Scientific (2008)

    Chapter  Google Scholar 

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Acknowledgements

This work has been supported by COMPETE: POCI-01-0145-FEDER-0070 43 and FCT Fundao para a Cincia e Tecnologia within the Project Scope UID/CEC/ 00319/2013.

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Correspondence to Leandro Oliveira Freitas .

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Freitas, L.O., Henriques, P.R., Novais, P. (2018). Uncertainty in Context-Aware Systems: A Case Study for Intelligent Environments. In: Rocha, Á., Adeli, H., Reis, L.P., Costanzo, S. (eds) Trends and Advances in Information Systems and Technologies. WorldCIST'18 2018. Advances in Intelligent Systems and Computing, vol 745. Springer, Cham. https://doi.org/10.1007/978-3-319-77703-0_22

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  • DOI: https://doi.org/10.1007/978-3-319-77703-0_22

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77702-3

  • Online ISBN: 978-3-319-77703-0

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