Abstract
Given a set of positive weighted points, the Maximizing Range Sum (maxRS) problem finds the placement of a query region r of given size such that the weight sum of points covered by r is maximized. This problem has long been studied since its wide application in spatial data mining, facility locating, and clustering problems. However, most of the existing work focus on Euclidean space, which is not applicable in many real-life cases. For example, in location-based services, the spatial data points can only be accessed by following certain underlying (road) network, rather than straight-line access. Thus in this paper, we study the maxRS problem with road network constraint, and propose an index-based method that solves the online queries highly efficiently.
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Notes
- 1.
W.l.o.g., we assume r and edge length are real numbers, and w(f) is constant integer.
- 2.
Note that there may exist multiple optimal locations, but we store only one in the index.
- 3.
We also test on another popular real dataset(California road network) from [15], where the 87635 facilities are carefully generated using the real-life facility distribution. The result trend is similar with other datasets hence omitted due to space limitation.
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Zhou, X., Wang, W. (2016). An Index-Based Method for Efficient Maximizing Range Sum Queries in Road Network. In: Cheema, M., Zhang, W., Chang, L. (eds) Databases Theory and Applications. ADC 2016. Lecture Notes in Computer Science(), vol 9877. Springer, Cham. https://doi.org/10.1007/978-3-319-46922-5_8
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