On the classification of text documents taking into account their structural features
- Authors: Gulin V.V.1, Frolov A.B.1
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Affiliations:
- Moscow Power Engineering Institute (National Research University)
- Issue: Vol 55, No 3 (2016)
- Pages: 394-403
- Section: Pattern Recognition and Image Processing
- URL: https://journals.rcsi.science/1064-2307/article/view/219634
- DOI: https://doi.org/10.1134/S1064230716030102
- ID: 219634
Cite item
Abstract
A modification of the conventional bag of words model that can take into account the structural features of text documents in their classification (categorization) using machine learning techniques is studied. It is proposed to describe these features by relations on the set of certain lexemes and use the relation names, along with the lexeme names, as features. This is a distinction from the conventional model in which only unary relations are used. The effectiveness of the proposed machine learning techniques is analyzed using computer experiments on the class of the Reuters-21578 collection with eight known classifiers. It is shown that it is reasonable to apply the proposed models to classify documents using simple classifiers.
About the authors
V. V. Gulin
Moscow Power Engineering Institute (National Research University)
Author for correspondence.
Email: gulin.vladimir@gmail.com
Russian Federation, Moscow, 111250
A. B. Frolov
Moscow Power Engineering Institute (National Research University)
Email: gulin.vladimir@gmail.com
Russian Federation, Moscow, 111250