Filtering Fitness Trail Content Generated by Mobile Users
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).
KeywordsMobile Device Context Information Mobile User Objective Feature Subjective Feature
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- 3.Nike, Inc.: Nike+ (2006), http://nikeplus.nike.com/nikeplus/index.jhtml?l=mapit
- 4.Huhtala, Y., Kaasinen, J.: Nokia Sports Tracker (2007), http://sportstracker.nokia.com/
- 5.Counts, S., Smith, M.: Where were we: communities for sharing space-time trails. In: GIS 2007: Proceedings of the 15th annual ACM international symposium on Advances in geographic information systems, pp. 1–8. ACM Press, New York (2007)Google Scholar
- 8.Sarwar, B., Karypis, G., Konstan, J., Reidl, J.: Item-based collaborative filtering recommendation algorithms. In: WWW 2001: Proceedings of the 10th international conference on World Wide Web, pp. 285–295. ACM Press, New York (2001)Google Scholar