DocumentCode
3425176
Title
Speeding-up text categorization in a grid computing environment
Author
Silva, Catarina ; Ribeiro, Bernardete ; Lotric, Uros
Author_Institution
Dept. of Comput. Sci., Polytech. Inst. of Leiria, Portugal
fYear
2005
fDate
15-17 Dec. 2005
Abstract
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.
Keywords
grid computing; learning (artificial intelligence); pattern classification; support vector machines; text analysis; SVM learning machine; digital text classifier; distributed text categorization; grid computing; support vector machine; Computer science; Distributed computing; Grid computing; Learning systems; Machine learning; Pervasive computing; Physics computing; Support vector machine classification; Support vector machines; Text categorization;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications, 2005. Proceedings. Fourth International Conference on
Print_ISBN
0-7695-2495-8
Type
conf
DOI
10.1109/ICMLA.2005.60
Filename
1607468
Link To Document