The advancements in the fields of mobile computing, grid computing, cloud computing, Internet of Things and primarily due to the availability of internet in the hand-held devices were the vital key factors in the growth of large amounts of data. The main challenge is to organize this big data in a structured manner that helps to derive new insights, predictive analysis and to find trends, patterns and their correlations. One of the solutions is to cluster the text, a significant technique of data mining. This paper investigates various techniques experimented in text clustering. It also describes the process of text clustering along with various similarity measures.