ALGORITHMS FOR VECTOR REPRESENTATION OF TEXT

Abstract

Natural language processing (NLP) is an attractive area of computing intelligence. This paper will introduce several ways to convert text to vectors. There are two major categories, the first based on statistical methods and the second using neural networks. The advantage of vector representation is the ability to compare or further use such vectors in one of the machine learning methods. Vector representation maintains some semantics, so it is a convenient method for representing and comparing more complex text.