Tremendous growth of text document collection has led to an increased interest in developing various approaches. Analysis and evaluation of useful information or patterns are must from the existing piles of raw data. To extract useful documents/ information/ patterns from the existing large amounts of unstructured retrospective corpora, various approaches such as Information Retrieval, Information Extraction and Text Mining were introduced. Different natural language processing techniques have been developed to improve the accuracy of extracting patterns. While several text handling approaches based on different features have been proposed in the past, there is no systematic study which discusses the similarities and distinctions of all these approaches. This paper discusses the overview of all these approaches, IR, IE, TM and NLP. We discuss about the methods and applications of existing approaches and also the theories in possible future research.