期刊文献+

基于PLC-iDistance的结构化P2P相似性检索算法

Similarity Search Algorithm on structure P2P networks Based on PLC-iDistance
下载PDF
导出
摘要 针对传统iDistance索引方法的缺陷和不足,提出了近似位置编码索引方法PLC-iDistance(Proximity Location Code-iDistance),并在结构化P2P网络中实现了高维数据检索。在改进方法中,有效地缩小了需要搜索的范围,提高了检索性能;.实验表明,相比传统的iDistance索引方法,PLC-iDistance索引方法在时间性能上有较大的提高。 In view of the traditional iDistance indexing methods' flaw and insufficiency, the paper proposes an indexing method: PLC-iDistanee (Proximity Location Code-iDistanee). With the indexing structure mentioned above, we achieved a high-dimensional data retrieving system on a structure P2P networks. The improved method greatly narrows searching scope between high-dimensional data. So it greatly improves the performance of data searching. The experimental result indicates that, compared with the traditional iDistance indexing method, the improved method has a bigger enhancement in terms of time performance.
作者 王福海
出处 《科技信息》 2011年第1期I0059-I0061,共3页 Science & Technology Information
关键词 高维数据 高维索引 相似性检索 High-dimensional data High-dimensional index Similarity search
  • 相关文献

参考文献7

二级参考文献32

  • 1周项敏,王国仁.基于关键维的高维空间划分策略[J].软件学报,2004,15(9):1361-1374. 被引量:16
  • 2董道国,刘振中,薛向阳.VA-Trie:一种用于近似k近邻查询的高维索引结构[J].计算机研究与发展,2005,42(12):2213-2218. 被引量:10
  • 3周项敏,王国仁,常立,范丹.批量构建M^+-tree[J].小型微型计算机系统,2006,27(2):295-299. 被引量:1
  • 4[1]Guttman A. R-Trees: A dynamic index structure for spatial searching. In: Yormark B, ed. Proc. of the ACM SIGMOD Conf. Boston,1984. 47~57.
  • 5[2]Berkmann N, Krigel HP. Schneider R, Seeger B. The R*-tree: An efficient and robust access method for points and rectangles. In Hector GM, Jagadish HV, eds. Proc. of the ACM SIGMOD Conf. Atlantic, 1990. 322~331.
  • 6[3]Katayama N, Satoh S. The SR-tree: An index structure for high-dimensional nearest neighbor queries. In: Peckham J, ed. Proc. of the ACM SIGMOD Conf. Tucson, 1997. 369~380.
  • 7[4]White DA, Jain R. Similarity indexing with the SS-tree. In: Stanley YWS, ed. Proc. of the 12th Int'l Conf. on Data Engineering New Orleans: IEEE Computer Society, 1996. 516~523.
  • 8[5]Lin K-I, Jagadish HV, Faloutsos C. The TV-tree: An index structure for high-dimensional data. VLDB Journal, 1994,3(4):517~542.
  • 9[6]Ciaceia P, Patella M, Zezula P. M-tree: An efficient access method for similarity search in metric spaces. In: Jarke M, Carey MJ,Dittrich KR, Lochovsky FH, Loucopoulos P, Jeusfeld MA, eds. Proc. of the 23rd VLDB Conf. Athens: Morgan Kaufmann Publishers, 1997.426~435.
  • 10[7]Bozkaya T, Ozsoyoglu M. Distance-Based indexing for high-dimensional metric spaces. In: Peckham J, ed. Proc. of the ACM SIGMOD Conf. on Management of Data Tucson, 1997. 357~368.

共引文献42

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部