Using the MF/MD method for automatic text classification

in Extending the scope of corpus-based research
Restricted Access
Get Access to Full Text

Subject Highlights

 

Abstract

In corpus linguistics, but also in computational linguistics and information retrieval, there is an increasing demand for the automatic classification of large amounts of text(s). In his research, Biber uses the Multi-Feature/Multi-Dimension (MF/MD) method to obtain a classification of English texts. A major disadvantage of his approach is the heavy reliance on the frequency count of complex grammatical features which are hard to retrieve automatically. In this paper, we investigate whether Biber’s MF/MD method can be used for automatic text classification. For this purpose, the MF/MD method is applied to the ICE-GB corpus, using three different sets of linguistic features. The results indicate that automatic text classification is indeed feasible using word class tags as input for the MF/MD method.

Extending the scope of corpus-based research

New applications, new challenges

Series:

Table of Contents

Index Card

Metrics

Metrics

All Time Past Year Past 30 Days
Abstract Views 18 18 3
Full Text Views 7 7 0
PDF Downloads 6 6 1
EPUB Downloads 0 0 0

Related Content