Name
Abstract | ||
|---|---|---|
The k-nearest neighbor (k-NN) query is one of the most important query types for location based services (LBS). Various methods have been proposed to efficiently process the k-NN query. However, most of the existing methods suffer from high computation time and larger memory requirement because they unnecessarily access cells to find the nearest cells on a grid index. In this paper, we propose a new efficient method, called Pattern Based k-NN (PB-kNN) to process the k-NN query. The proposed method uses the patterns of the distance relationships among the cells in a grid index. The basic idea is to normalize the distance relationships as certain patterns. Using this approach, PB-kNN significantly improves the overall performance of the query processing. It is shown through various experiments that our proposed method outperforms the existing methods in terms of query processing time and storage overhead. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2063576.2063980 | CIKM |
Keywords | Field | DocType |
query processing time,existing method,k-nearest neighbor query processing,distance relation pattern,various method,important query type,distance relationship,query processing,grid index,k-nn query,new efficient method,location based service,k nearest neighbor,indexation,location based services | Query optimization,Data mining,Information retrieval,Query expansion,Computer science,Sargable,Web query classification,Ranking (information retrieval),Spatial query,Online aggregation,Nearest neighbor search | Conference |
Citations | PageRank | References |
1 | 0.35 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yonghun Park | 1 | 20 | 4.33 |
| Dongmin Seo | 2 | 49 | 10.64 |
| Kyoungsoo Bok | 3 | 55 | 16.55 |
| Jaesoo Yoo | 4 | 123 | 35.63 |