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    Online Trajectory Classification


    Sas, Corina and O'Hare, Gregory and Reilly, Ronan (2003) Online Trajectory Classification. In: ICCS 2003: Computational Science. Lecture Notes in Computer Science book series (LNCS) (2659). Springer, pp. 1035-1044. ISBN 3540401970

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    Abstract

    This study proposes a modular system for clustering on-line motion trajectories obtained while users navigate within a virtual environment. It presents a neural network simulation that gives a set of five clusters which help to differentiate users on the basis of efficient and inefficient navigational strategies. The accuracy of classification carried out with a self-organizing map algorithm was tested and improved to above 85% by using learning vector quantization. The benefits of this approach and the possibility of extending the methodology to the study of navigation in Human Computer Interaction are discussed.

    Item Type: Book Section
    Additional Information: Cite this paper as: Sas C., O’Hare G., Reilly R. (2003) Online Trajectory Classification. In: Sloot P.M.A., Abramson D., Bogdanov A.V., Gorbachev Y.E., Dongarra J.J., Zomaya A.Y. (eds) Computational Science — ICCS 2003. ICCS 2003. Lecture Notes in Computer Science, vol 2659. Springer, Berlin, Heidelberg
    Keywords: online; trajectory; classification; on-line motion trajectories; virtual environments;
    Academic Unit: Faculty of Science and Engineering > Computer Science
    Item ID: 8213
    Identification Number: https://doi.org/10.1007/3-540-44863-2_102
    Depositing User: Prof. Ronan Reilly
    Date Deposited: 15 May 2017 14:44
    Publisher: Springer
    Refereed: Yes
    URI:

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