Name
Abstract | ||
|---|---|---|
In this paper, we introduce a novel query type, the moving view field nearest neighbor (MVFNN) query —a continuous version of the view field nearest neighbor (VFNN) query. This query continuously retrieves the nearest object in the query’s view field taking into account the changes of the query location and view field. In order to improve the performance of the query processing, we propose the notion of geographical and angular safe boundaries. We can skip redundant computation if the moved query satisfies the geographical and angular safe boundaries. Our method is easily applicable to existing services since we do not transform the general index structures. We prove the efficiency of our method by a series of experiments varying the parameters such as query’s moving speed, view field angle, and the distribution of data objects. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.datak.2018.12.002 | Data & Knowledge Engineering |
Keywords | Field | DocType |
Moving view field nearest neighbor query,Spatial databases,Continuous query,Augmented reality,Location-based service | k-nearest neighbors algorithm,Data mining,Information retrieval,Computer science,Location-based service,Augmented reality,Data objects,Computation | Journal |
Volume | Issue | ISSN |
119 | 1 | 0169-023X |
Citations | PageRank | References |
0 | 0.34 | 11 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wooil Kim | 1 | 120 | 16.95 |
| Changbeom Shim | 2 | 6 | 3.48 |
| Wan Heo | 3 | 4 | 0.74 |
| Sungmin Yi | 4 | 18 | 4.03 |
| Yon Dohn Chung | 5 | 666 | 48.55 |