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http://dx.doi.org/10.3745/KIPSTD.2004.11D.2.269

Efficient Searching Technique for Nearest Neighbor Object in High-Dimensional Data  

Kim, Jin-Ho (명지대학교 대학원 컴퓨터공학과)
Park, Young-Bae (명지대학교 컴퓨터공학과)
Publication Information
The KIPS Transactions:PartD / v.11D, no.2, 2004 , pp. 269-280 More about this Journal
Abstract
The Pyramid-Technique is based on mapping n-dimensional space data into one-dimensional data and expresses it as a B+-tree. By solving the problem of search time complexity the pyramid technique also prevents the effect of "phenomenon of dimensional curse" which is caused by treatment of hypercube range query in n-dimensional data space. The SPY-TEC applies the space division strategy in pyramid method and uses spherical range query suitable for similarity search so that Improves the search performance. However, nearest neighbor query is more efficient than range query because it is difficult to specify range in similarity search. Previously proposed index methods perform well only in the specific distribution of data. In this paper, we propose an efficient searching technique for nearest neighbor object using PdR-Tree suggested to improve the search performance for high dimensional data such as multimedia data. Test results, which uses simulation data with various distribution as well as real data, demonstrate that PdR-Tree surpasses both the Pyramid-Technique and SPY-TEC in views of search performance.rformance.
Keywords
PdR-Tree; Pyramid-Technique; SPY-TEC; Nearest Neighbor Query;
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Times Cited By KSCI : 1  (Citation Analysis)
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