Name
Abstract | ||
|---|---|---|
A k-nearest neighbor (kNN) query determines the k nearest points, using distance metrics, from a given location. An all k-nearest neighbor (AkNN) query constitutes a variation of a kNN query and retrieves the k nearest points for each point inside a database. Their main usage resonates in spatial databases and they consist the backbone of many location-based applications and not only. Although (A) kNN is a fundamental query type, it is computationally very expensive. During the last years a multiplicity of research papers has focused around the distributed (A) kNN query processing on the cloud. This work constitutes a survey of research efforts towards this direction. The main contribution of this work is an up-to-date review of the latest (A) kNN query processing approaches. Finally, we discuss various research challenges and directions of further research around this domain. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-57045-7_3 | ALGORITHMIC ASPECTS OF CLOUD COMPUTING, ALGOCLOUD 2016 |
Keywords | Field | DocType |
Big data,Nearest neighbor,MapReduce,NoSQL,Query processing | k-nearest neighbors algorithm,Information retrieval,Computer science,NoSQL,Big data,Cloud computing,Distributed computing | Conference |
Volume | ISSN | Citations |
10230 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nikolaos Nodarakis | 1 | 23 | 6.00 |
| Angeliki Rapti | 2 | 4 | 3.12 |
| Spyros Sioutas | 3 | 206 | 77.88 |
| Athanasios K. Tsakalidis | 4 | 544 | 117.52 |
| Dimitrios Tsolis | 5 | 34 | 13.93 |
| Giannis Tzimas | 6 | 111 | 28.31 |
| Yannis Panagis | 7 | 0 | 1.01 |