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Sas, Corina, 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: | 10.1007/3-540-44863-2_102 |
| Depositing User: | Prof. Ronan Reilly |
| Date Deposited: | 15 May 2017 14:44 |
| Publisher: | Springer |
| Refereed: | Yes |
| Related URLs: | |
| URI: | https://mural.maynoothuniversity.ie/id/eprint/8213 |
| Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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