Name
Abstract | ||
|---|---|---|
The growing need for location based services motivates the moving nearest neighbor query (MNN), which requires to find the nearest neighbors of a moving query point continuously. In most existing solutions, data objects are abstracted as points. However, lots of real-world data objects, such as roads, rivers or pipelines, should be reasonably modeled as line segments or polyline segments. In this paper, we present LV*-Diagram to handle MNN queries over data objects. LV*-Diagram dynamically constructs a safe region. The query results remain unchanged if the query point is in the safe region, and hence, the computation cost of the server is greatly reduced. Experimental results show that our approach significantly outperforms the baseline method w.r.t. CPU load, I/O, and communication costs. |
Year | DOI | Venue |
|---|---|---|
2016 | https://doi.org/10.1007/s11280-015-0351-3 | World Wide Web |
Keywords | Field | DocType |
k nearest neighbor,Line segments,Continuous queries,Spatial queries | k-nearest neighbors algorithm,Data mining,Line segment,Computer science,Location-based service,Artificial intelligence,Cpu load,Data objects,Machine learning,Computation | Journal |
Volume | Issue | ISSN |
19 | 4 | 1386-145X |
Citations | PageRank | References |
3 | 0.37 | 24 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yu Gu | 1 | 201 | 34.98 |
| Hui Zhang | 2 | 3 | 0.37 |
| Zhigang Wang | 3 | 21 | 3.97 |
| Ge YU | 4 | 1313 | 175.88 |