Abstract
In this paper, we propose route of interest (ROI) query which allows users to specify their interests with query keywords and returns a route such that (i) its distance is less than a distance threshold and (ii) its relevance to the query keywords is maximized. ROI query is particularly helpful for tourists and city explorers. For example, a tourist may wish to find a route from a scenic spot to her hotel to cover many artware shops. It is challenging to efficiently answer ROI query due to its NP-hard complexity. Novelly, we propose an adaptive route sampling framework that adaptively computes a route according to a given response time, and gradually improve the quality of the route with time. Moreover, we design a suite of route sampling techniques under this framework. Experiments on real data suggest that our proposed solution can return high quality routes within a short response time.
Keywords
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Acknowledgments
This work is partially supported by the National Natural Science Foundation of China under Grant No.61373036 and the NSFC/RGC Joint Research Scheme No. N_PolyU519/12.
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Li, W., Cao, J., Guan, J., Yiu, M.L., Zhou, S. (2016). Retrieving Routes of Interest Over Road Networks. In: Cui, B., Zhang, N., Xu, J., Lian, X., Liu, D. (eds) Web-Age Information Management. WAIM 2016. Lecture Notes in Computer Science(), vol 9658. Springer, Cham. https://doi.org/10.1007/978-3-319-39937-9_9
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DOI: https://doi.org/10.1007/978-3-319-39937-9_9
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