Categorization of news articles using neural text categorizer

Abstract

This research proposes the application of NTC (neural text categorizer) for categorizing news articles. Even if the research on text categorization has been progressed very much, documents should be still encoded into numerical vectors. Encoding so causes the two main problems: huge dimensionality and sparse distribution. The idea of this research as the solution to the problems is to encode documents into string vectors and apply the NTC as a string vector based approach to text categorization. The idea will be described in detail and validated.