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  • 标题:Clustering: Applied to Data Structuring and Retrieval
  • 本地全文:下载
  • 作者:Ogechukwu N Iloanusi ; Charles C. Osuagwu
  • 期刊名称:International Journal of Advanced Computer Science and Applications(IJACSA)
  • 印刷版ISSN:2158-107X
  • 电子版ISSN:2156-5570
  • 出版年度:2011
  • 卷号:2
  • 期号:11
  • DOI:10.14569/IJACSA.2011.021116
  • 出版社:Science and Information Society (SAI)
  • 摘要:Clustering is a very useful scheme for data structuring and retrieval behuhcause it can handle large volumes of multi-dimensional 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.
  • 关键词:thesai; IJACSA; thesai.org; journal; IJACSA papers; component; Clustering; k-means; data retrieval; indexing.
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