Abstract
This paper proposes a novel trail sharing system for mobile devices that deals with context information collected by sensors, as well as users’ personal opinions (e.g., landscape beauty) specified by ratings. To help the user in finding trails that are more suited to her, the system exploits a collaborative filtering approach to predict the ratings users may give to untried trails, and applies a similar approach also to context information that can significantly vary among users (e.g., lap duration).
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Buttussi, F., Chittaro, L., Nadalutti, D. (2009). Filtering Fitness Trail Content Generated by Mobile Users. In: Houben, GJ., McCalla, G., Pianesi, F., Zancanaro, M. (eds) User Modeling, Adaptation, and Personalization. UMAP 2009. Lecture Notes in Computer Science, vol 5535. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02247-0_50
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DOI: https://doi.org/10.1007/978-3-642-02247-0_50
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