Clustering: Applied to Data Structuring and

被引:0
|
作者
Iloanusi, Ogechukwu N. [1 ]
Osuagwu, Charles C. [1 ]
机构
[1] Univ Nigeria, Dept Elect Engn, Nsukka, Enugu State, Nigeria
关键词
component; Clustering; k-means; data retrieval; indexing;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Clustering is a very useful scheme for data structuring and retrieval behuhcause it can handle large volumes of multidimensional data and employs a very fast algorithm. Other forms of data structuring techniques include hashing and binary tree structures. However, clustering has the advantage of employing little computational storage requirements and a fast speed algorithm. In this paper, clustering, k-means clustering and the approaches to effective clustering are extensively discussed. Clustering was employed as a data grouping and retrieval strategy in the filtering of fingerprints in the Fingerprint Verification Competition 2000 database 4(a). An average penetration of 7.41% obtained from the experiment shows clearly that the clustering scheme is an effective retrieval strategy for the filtering of fingerprints.
引用
收藏
页码:100 / 105
页数:6
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