Name
Abstract | ||
|---|---|---|
Location recommendation is essential for various map-based mobile applications. However, it is not easy to generate location-based recommendations with the changing contexts and locations of mobile users. Skyline operation is one of the most well-established techniques for location-based services. Our previous work proposed a new query method, called "area skyline query", to select areas in a map. However, it is not efficient for large-scale data. In this paper, we propose a parallel algorithm for processing the area skyline using MapReduce. Intensive experiments on both synthetic and real data confirm that our proposed algorithm is sufficiently efficient for large-scale data. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.3390/a11120191 | ALGORITHMS |
Keywords | Field | DocType |
area skyline,grid structure,MapReduce | Skyline,Parallel algorithm,Algorithm,Artificial intelligence,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
11 | 12 | 1999-4893 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chen Li | 1 | 2816 | 196.16 |
| annisa | 2 | 4 | 2.77 |
| Asif Zaman | 3 | 6 | 5.16 |
| Mahboob Qaosar | 4 | 3 | 2.40 |
| Saleh Ahmed | 5 | 2 | 2.39 |
| Yasuhiko Morimoto | 6 | 528 | 341.88 |