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An Unsupervised Learning Paradigm for Peer-to-Peer Labeling and Naming of Locations and Contexts

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Location- and Context-Awareness (LoCA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3987))

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Abstract

Several approaches to context awareness have been proposed ranging from unsupervised learning to ontologies. Independent of the type of context awareness used a consistent approach to naming contexts is required. A novel paradigm for labeling contexts is described based on close range wireless connections between devices and a very simple, unsupervised learning algorithm. It is shown by simulation analysis that it is possible to achieve a labeling of different contexts which allows context related information to be communicated in a consistent manner between devices. As the learning is unsupervised no user input is required for it to work. Furthermore this approach requires no extra infrastructure or resources to manage the names assigned to the contexts.

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References

  1. Dey, A.: Understanding and using context. Personal and Ubiquitous Computing 5, 4–7 (2001)

    Article  Google Scholar 

  2. Staab, S.: Handbook on Ontologies. Springer, Heidelberg (2004)

    Book  MATH  Google Scholar 

  3. Persson, P., Blom, J., Jung, Y.: DigiDress: A field trial of an expressive social proximity application. In: Beigl, M., Intille, S.S., Rekimoto, J., Tokuda, H. (eds.) UbiComp 2005. LNCS, vol. 3660, pp. 195–212. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  4. Eagle, N., Pentland, A.: Social serendipity: Mobilizing social software. IEEE Pervasive Computing 4, 28–34 (2005)

    Article  Google Scholar 

  5. Moloney, S.: Simulation of a distributed recommendation system for pervasive networks. In: ACM Symposium on Applied Computing, Santa Fe, New, Mexico, USA, pp. 1577–1581 (2005)

    Google Scholar 

  6. Chen, H., Finin, T., Joshi, A.: An ontology for context-aware pervasive computing environments. Knowledge Engineering Review, Special Issue on Ontologies for Distributed Systems 18, 197–207 (2004)

    Google Scholar 

  7. Wang, X., Zhang, D.Q., Gu, T., Pung, H.K.: Ontology-based context modeling and reasoning using OWL. In: Workshop on Context Modeling and Reasoning at IEEE International Conference on Pervasive Computing and Communication (PerCom 2004), Orlando, Florida, US (2004)

    Google Scholar 

  8. Korpipää, P., Mäntyjärvi, J.: An ontology for mobile device sensor-based context awareness. In: Blackburn, P., Ghidini, C., Turner, R.M., Giunchiglia, F. (eds.) CONTEXT 2003. LNCS, vol. 2680, pp. 451–458. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  9. Flanagan, J.: Context awareness in a mobile device: Ontologies versus unsupervised/supervised learning. In: Honkela, T., Könönen, V., Pöllä, M., O.S. (eds.) Intl’ and Interdisciplinary Conf. on Adpative Knowledge Representation and Reasoning (AKKR 2005), Espoo, Finland, Otamedia Oy, pp. 167–170 (2005)

    Google Scholar 

  10. Flanagan, J.A.: Unsupervised clustering of context data and learning user requirements for a mobile device. In: Dey, A.K., Kokinov, B., Leake, D.B., Turner, R. (eds.) CONTEXT 2005. LNCS, vol. 3554, pp. 155–168. Springer, Heidelberg (2005)

    Chapter  Google Scholar 

  11. Flanagan, J.A., Mäntyjärvi, J., Himberg, J.: Unsupervised clustering of symbol strings and context recognition. In: IEEE Intl’ Conf. on Data Mining (ICDM 2002), Maebashi City, Japan, pp. 171–178 (2002)

    Google Scholar 

  12. Battestini, A., Flanagan, J.: Analysis and cluster based modelling and recognition of context in a mobile environment. In: Roth-Berghofer, T., Schulz, S., Leake, D. (eds.) Proc. of the 2nd Intl’ Workshop on Modeling and Retrieval of Context (MRC), pp. 85–96 (2005), ISSN: 1613-0073, online: CEUR-WS.org//Vol-146//

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© 2006 Springer-Verlag Berlin Heidelberg

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Flanagan, J.A. (2006). An Unsupervised Learning Paradigm for Peer-to-Peer Labeling and Naming of Locations and Contexts. In: Hazas, M., Krumm, J., Strang, T. (eds) Location- and Context-Awareness. LoCA 2006. Lecture Notes in Computer Science, vol 3987. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752967_14

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  • DOI: https://doi.org/10.1007/11752967_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34150-5

  • Online ISBN: 978-3-540-34151-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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