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Spatial Navigation Assistance System for Large Virtual Environments: The Data Mining Approach

Spatial Navigation Assistance System for Large Virtual Environments: The Data Mining Approach

Mehmed Kantardzic, Pedram Sadeghian, Walaa M. Sheta
Copyright: © 2008 |Pages: 19
ISBN13: 9781599045283|ISBN10: 1599045281|ISBN13 Softcover: 9781616926564|EISBN13: 9781599045306
DOI: 10.4018/978-1-59904-528-3.ch016
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MLA

Kantardzic, Mehmed, et al. "Spatial Navigation Assistance System for Large Virtual Environments: The Data Mining Approach." Mathematical Methods for Knowledge Discovery and Data Mining, edited by Giovanni Felici and Carlo Vercellis, IGI Global, 2008, pp. 265-283. https://doi.org/10.4018/978-1-59904-528-3.ch016

APA

Kantardzic, M., Sadeghian, P., & Sheta, W. M. (2008). Spatial Navigation Assistance System for Large Virtual Environments: The Data Mining Approach. In G. Felici & C. Vercellis (Eds.), Mathematical Methods for Knowledge Discovery and Data Mining (pp. 265-283). IGI Global. https://doi.org/10.4018/978-1-59904-528-3.ch016

Chicago

Kantardzic, Mehmed, Pedram Sadeghian, and Walaa M. Sheta. "Spatial Navigation Assistance System for Large Virtual Environments: The Data Mining Approach." In Mathematical Methods for Knowledge Discovery and Data Mining, edited by Giovanni Felici and Carlo Vercellis, 265-283. Hershey, PA: IGI Global, 2008. https://doi.org/10.4018/978-1-59904-528-3.ch016

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Abstract

Advances in computing techniques, as well as the reduction in the cost of technology have made possible the viability and spread of large virtual environments. However, efficient navigation within these environments remains problematic for novice users. Novice users often report being lost, disorientated, and lacking the spatial knowledge to make appropriate decisions concerning navigation tasks. In this chapter, we propose the Frequent Wayfinding-Sequence (FWS) methodology to mine the sequences representing the routes taken by experienced users of a virtual environment in order to derive informative navigation models. The models are used to build a navigation assistance interface. We conducted several experiments using our methodology in simulated virtual environments. The results indicate that our approach is efficient in extracting and formalizing recommend routes of travel from the navigation data of previous users of large virtual environments.

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