Text classification in the domain of applied linguistics as part of a pre-editing module for machine translation systems

Abstract

This article describes the method of document classification on the basis of a vector space model with regard to the domain of Applied Linguistics for Russian. This method makes it possible to classify input text data in two different categories: applied linguistics texts (AL) and non-applied linguistics texts (nonAL). The proposed method is implemented using the statistical measure of TF-IDF and the evaluation measure of cosine similarity. The study gives promising results and opens up further prospects for the application of this approach to text classification in other languages.