Research on Short Text Classification Algorithm Based on Statistics and Rules

In this paper, we introduced the overview of short text research and the short text classification firstly. On the foundation of several common used classic text classification algorithms, mainly according to the major feature extraction methods, the short text classification based on statistics and rules is proposed. Experiments show that this algorithm has better performance than other algorithms. In order to improve the recall rate of short text classification, two-steps classification method is put forward.

I. Introduction

Classification is an important cognitive way of knowing the unknown world by people. For example, people classify creatures into plants and animals and further into phylum, class, order, family, genus, and species according to their different characteristics. In sociology, people with different beliefs are classified into different parties, religions, etc. In real production and life, if similar things are put into one category and things with obvious differences are put into different categories, it will be much simpler to deal with them.