چکيده
Abstract The rapid growth of textual data in the world has increased the need to use data collection techniques. Text clustering is one of the practical techniques that can improve the performance of data collection while on the one hand reduce the dimensions of textual data. Text clustering is a process in which sets of words are divided into groups in which the words in each group are closely related and do not have a strong relationship with other words in other clusters. The relationship between words can be lexical, syntactic or semantic. In this article, firstly, the concept and techniques of data clustering will be introduced in order to define the subject matter correctly .In the second chapter, common text clustering techniques are reviewed along with the background of the research . Finally, in the third chapter, clustering techniques based on deep learning are categorized along with their related works .From what has been discussed throughout this article, a general summary is made in the conclusion section.
