• The Transactions of the Korea Information Processing Society
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• v.4 no.9
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• pp.2173-2184
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• 1997

Among spatial queries handled in spatial database systems, nearest neighbor queries to find the nearest spatial object from the given locaion occur frequently. The number of searched nodes in an index must be minimized in order to increase the performance of nearest neighbor queries. An Existing approach considered only the processing of an nearest neighbor query in a two-dimensional search space and could not optimize the number of searched nodes accurately. In this paper, we propose the optimal search distance and prove its properties. The proposed optimal search distance is the measurement of a new search distance for accurately selecting the nodes which will be searched in processing nearest neighbor queries. We present an algorithm for processing the nearest neighbor query by applying the optimal search distance to R-trees and prove that the result of query processing is correcter than the existing approach.

• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.85-88
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• 2009

In multimedia database systems, the nearest neighbor Query occurs frequently and requires the processing cost higher than other spatial Queries do. It needs the measurement of search distance that the number of searched nodes and the computation time in an index can be minimized for optimizing the cost of processing the nearest neighbor query. The circular location property of objects is considered to accurately select the nodes which will be searched in the nearest neighbor query. In this paper, we propose the processing method of nearest neighbor queries be considered a circular location property of object where the search space consists of a circular domain and show its characteristics. The proposed method uses the circular minimum distance and the circular optimal distance, the search measurement for optimizing the processing cost of nearest neighbor queries.

• Convergence Security Journal
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• v.17 no.2
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• pp.81-88
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• 2017

It is occurred frequently the reverse nearest neighbor queries to find objects where a query point can be the nearest neighbor object in recently applications like the encrypted spatial database. In a search space of the real world, however, there are many physical obstacles(e.g., rivers, lakes, highways, etc.). It is necessary the accurate measurement of distances considered the obstacles to increase the retrieval performance such as this circumstance. In this study, we present the algorithm and the measurement of distance to optimize the processing performance of reverse nearest neighbor queries in a search space with the presence of obstacles.

• Journal of the Korea Computer Industry Society
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• v.4 no.4
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• pp.443-448
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• 2003

Approximate k-nearest neighbor queries are frequently occurred for finding the k nearest neighbors to a given query point in spatial database systems. The number of searched nodes in an index must be minimized in order to increase the performance of approximate k nearest neighbor queries. In this paper. we suggest the technique of approximate k nearest neighbor queries on R-tree family by improving the existing algorithm and evaluate the performance of the proposed method in dynamic spatial database environments. The simulation results show that a proposed method always has a low number of disk access irrespective of object distribution, size of nearest neighbor queries and approximation rates as compared with an existing method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.4
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• pp.300-307
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• 2012

When the volume of data grows big, some simple tasks could become a significant concern. Nearest neighbor search is such a task which finds from a data set the k nearest data points to queries. Locality-sensitive hashing techniques have been developed for approximate but fast nearest neighbor search. This paper introduces the notion of locality-sensitive hashing and surveys the locality-sensitive hashing techniques. It categories them based on several criteria, presents their characteristics, and compares their performance.

• Journal of the Korea Society of Computer and Information
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• v.26 no.4
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• pp.63-74
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• 2021

Location-based services (LBSs) are expected to process a large number of spatial queries, such as shortest path and k-nearest neighbor queries that arrive simultaneously at peak periods. Deploying more LBS servers to process these simultaneous spatial queries is a potential solution. However, this significantly increases service operating costs. Recently, batch processing solutions have been proposed to process a set of queries using shareable computation. In this study, we investigate the problem of batch processing moving k-nearest neighbor (MkNN) queries in dynamic spatial networks, where the travel time of each road segment changes frequently based on the traffic conditions. LBS servers based on one-query-at-a-time processing often fail to process simultaneous MkNN queries because of the significant number of redundant computations. We aim to improve the efficiency algorithmically by processing MkNN queries in batches and reusing sharable computations. Extensive evaluation using real-world roadmaps shows the superiority of our solution compared with state-of-the-art methods.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.11-20
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• 2008

• The KIPS Transactions:PartD
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• v.16D no.2
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• pp.191-200
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• 2009

Location based services (LBSs) have drawn huge attention as the growing number mobile devices and wireless technology demand more pervasive information access. In LBSs, Constraint nearest neighbor queries are one of the important queries of human to fulfill his desired quickly through wireless technology. We propose new query processing of constrained nearest neighbor query on the air to support mobile clients which demand optimal uses of wireless broadcast channel and using minimum battery power of client. First we proposed NN query processing with constrained region and then explain the novel NN query processing with various types of constraints. We have proposed novel algorithms to support Constrained Nearest Neighbor queries on the air based on Distributed Spatial Index and Bitmap-based Spatial Index.

• Journal of the Korea Computer Industry Society
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• v.5 no.9
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• pp.1025-1030
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• 2004

In multimedia database systems, the k nearest neighbor query occurs frerluently and requires the processing cost higher than other spatial queries do. The numberof searched nodes and the computation time in an index can be minimized for optimizing the cost of processing the k nearest neighbor query. In this paper, we propose the search distance which can reduce the computation time of the optimal search distance.

• Journal of Industrial Technology
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• v.20 no.B
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• pp.213-218
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• 2000

The nearest neighbor query is an important operation widely used in multimedia databases for finding the object that is most similar to a given query object. Most of techniques for processing nearest neighbor queries employ multidimensional indexes for effective indexing of objects. However, the performance of previous multidimensional indexes, which use N-dimensional rectangles or spheres for representing the capsule of the object cluster, deteriorates seriously as the number of dimensions gets higher. This paper proposes a new index structure based singular value decomposition resolving this problem and the query processing method using it. We also verify the superiority of our approach through performance evaluation by performing extensive experiments.