Speeding-up text categorization in a GRID computing environment

被引：0

作者：

Silva, C ^{[1
]}

Ribeiro, B ^{[1
]}

Lotric, U ^{[1
]}

机构：

[1] Polytech Inst, Dept Comp Sci, ESTG, Leiria, Portugal

来源：

ICMLA 2005: FOURTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, PROCEEDINGS | 2005年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The amount of texts available in digital form has dramatically increased, giving rise to the need of fast text classifiers. The tasks involved can be parallelized and distributed in a GRID environment. This paper reports a study conducted on Reuters-21578 corpus, using a SVM learning machine. The task of text categorization is distributed in several platforms. The results achieved are very promising for speeding-up text categorization tasks and are valid independently of the learning machine.

引用

页码：311 / 316

页数：6

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