Parallel nearest neighbour algorithms for text categorization

被引：0

作者：

Gil-Garcia, Reynaldo ^{[1
]}

Badia-Contelles, Jose Manuel ^{[2
]}

Pons-Porrata, Aurora ^{[1
]}

机构：

[1] Univ Oriente, Ctr Pattern Recognit & Data Mining, Santiago De Cuba, Cuba

[2] Univ Jaume 1, Dept Comp Sci & Engn, Castellon de La Plana, Spain

来源：

EURO-PAR 2007 PARALLEL PROCESSING, PROCEEDINGS | 2007年 / 4641卷

关键词：

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper we describe the parallelization of two nearest neighbour classification algorithms. Nearest neighbour methods are well-known machine learning techniques. They have been successfully applied to Text Categorization task. Based on standard parallel techniques we propose two versions of each algorithm on message passing architectures. We also include experimental results on a cluster of personal computers using a large text collection. Our algorithms attempt to balance the load among the processors, they are portable, and obtain very good speedups and scalability.

引用

页码：328 / +

页数：2

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