Sciweavers

Share
ML
2002
ACM

Text Categorization with Support Vector Machines. How to Represent Texts in Input Space?

8 years 11 months ago
Text Categorization with Support Vector Machines. How to Represent Texts in Input Space?
The choice of the kernel function is crucial to most applications of support vector machines. In this paper, however, we show that in the case of text classification, term-frequency transformations have a larger impact on the performance of SVM than the kernel itself. We discuss the role of importance-weights (e.g. document frequency and redundancy), which is not yet fully understood in the light of model complexity and calculation cost, and we show that time consuming lemmatization or stemming can be avoided even when classifying a highly inflectional language like German.
Edda Leopold, Jörg Kindermann
Added 22 Dec 2010
Updated 22 Dec 2010
Type Journal
Year 2002
Where ML
Authors Edda Leopold, Jörg Kindermann
Comments (0)
books