Abstract
The proliferation of GPS-enabled mobile devices has contributed to accumulation of large-scale data on trajectories of moving objects, and presented an unprecedented opportunity to discover and share new knowledge, such as location significance. Existing technologies lack the ability to provide meaningful rankings on locations respective to user communities due to lack of consideration for some fundamental characteristics of trajectory data such as uncertainty, lack of semantics and lack of context. These problems can be addressed by building solutions on quality enhanced trajectory data and achieving ranking of physical locations in the geographical space similar to what was achieved by page ranking in cyberspace. In this talk we will look at emerging issues, recent research results and new opportunities in this multidisciplinary research area involving trajectory data processing, data quality management and information ranking.
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© 2011 Springer Science+Business Media B.V.
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Zhou, X. (2011). Location Significance Ranking from Quality Enhanced Trajectory Data. In: Park, J., Jin, H., Liao, X., Zheng, R. (eds) Proceedings of the International Conference on Human-centric Computing 2011 and Embedded and Multimedia Computing 2011. Lecture Notes in Electrical Engineering, vol 102. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2105-0_2
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DOI: https://doi.org/10.1007/978-94-007-2105-0_2
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