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Bayesian nearest Neighbor Search in a Spatial Database
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 7 |
| Year of Publication: 2012 |
| Authors: K. Balasaravanan, K. Duraiswamy |
10.5120/104-0201
|
K. Balasaravanan, K. Duraiswamy . Bayesian nearest Neighbor Search in a Spatial Database. International Journal of Applied Information Systems. 1, 7 ( March 2012), 7-10. DOI=10.5120/104-0201
Abstract
In an uncertain spatial database, identifying nearest neighbor is the important task to perform. To perform the nearest neighbor search (NN), existing work have presented Authenticated Multi-step NN (AMNN) and Superseding Nearest Neighbor (SNN) search. The AMNN efficiently performed the NN search using query authentication and trusted authority centre in which NN search has done only in single server not for distributed server and communication overhead also increased. The main drawback of SNN is that it cannot be applied to high dimensional data structure. To overcome all these issues, in this paper we implements a new technique named BNN (Bayesian Nearest Neighbor) for NN search and similarity search in a spatial database. BNN performs NN search efficiently and retrieve the distance information not only from single server but also from distributed servers. It can be applied to high dimensional data structure and it automatically reduces the communication overhead. The query result returned by BNN will be a reliable one. The experimental evaluation shows that BNN performs Nearest neighbor search and similarity search well than existing AMNN and SNN.
References
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