Volume 8 Number 8 (Aug. 2013)
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JCP 2013 Vol.8(8): 2085-2092 ISSN: 1796-203X
doi: 10.4304/jcp.8.8.2085-2092

Clustering-based Nearest Neighbor Searching

Ping Ling1, Xiangsheng Rong2, and Yongquan Dong1
1 College of Computer Science and Technology, Jiangsu Normal University, Xuzhou, 221116, China
2 Training Department, Air Force Logistics of P. L. A, Xuzhou 221000, China


Abstract—This paper proposes a Clustering-based Nearest Neighbor Search algorithm (CNNS) for high dimensional data. Different from existing approaches that are based on rigid-grid partition to develop data access structure, CNNS creates indexing structures according to data inherent distribution, with help of a progressive-styled clustering operation. The grids produced in this way adapt to data natural contours. CNNS is characterized with dataset reduction and dimension reduction. And parameterization heuristics are given to bring computation ease to CNNS. Empirical evidence on real datasets demonstrates the fine performance of CNNS.

Index Terms—clustering-based method, nearest neighbor searching, grid partion, parameterization heuristics

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Cite: Ping Ling, Xiangsheng Rong, and Yongquan Dong, " Clustering-based Nearest Neighbor Searching," Journal of Computers vol. 8, no. 8, pp. 2085-2092, 2013.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat,etc
E-mail: jcp@iap.org
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