Name
Abstract | ||
|---|---|---|
The MaxBRNN problem is to find an optimal region such that setting up a new service site within this region might attract the maximal number of customers by proximity. It has many practical applications such as service location planning and emergency schedule. Typical real-life applications are most in planar space, and the data volume of the problem is huge and thus an efficient solution is highly desired. In this paper, we propose an efficient algorithm, namely, OptRegion, to tackle the MaxBRNN problem in a two-dimensional space. Our methods employ three optimization techniques, i.e., sweep line, pruning strategy (based on upper bound estimation), and influence value computation (of candidate points), to improve the search performance. Extensive experimental evaluation using both real and synthetic datasets confirms that OptRegion outperforms the existing ones significantly under all problem instances. © Springer-Verlag 2013. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1007/978-3-642-37487-6_13 | DASFAA |
Field | DocType | Volume |
Data mining,Computer science,Upper and lower bounds,Range query (data structures),Algorithm,Planar,Sweep line algorithm,Service location,Computation | Conference | 7825 LNCS |
Issue | ISSN | Citations |
PART 1 | 16113349 | 8 |
PageRank | References | Authors |
0.45 | 14 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Huaizhong Lin | 1 | 67 | 12.34 |
| Fangshu Chen | 2 | 12 | 2.20 |
| Yunjun Gao | 3 | 862 | 89.71 |
| Dongming Lu | 4 | 163 | 32.29 |