At present, text mining has developed into an significant research topic. Text Mining is the discovery using computer of new, previously unidentified information, by automatically extracting information from several written resources. Data mining and text mining have been of massive value in several business sectors. In order to make data mining (discovering ?facts? and ?insights? from structured data) and text mining (discovering ?facts? and ?insights? from unstructured data), important resources are necessary. While considering industries like pharmaceuticals, these massive efforts which can cost tens of millions of dollars comprise proprietary information and extremely larger quantities of open source data. Here, advance structure of text mining with its framework, techniques and applications areas have been completely presented. A new and fast emerging field a text mining framework is formulated by highlighting on its most important step: information extraction, retrieval, mining and interpretation. And four major text mining approaches: feature extraction, thematic indexing, clustering and summarization will be explored clearly too. And also represented the significance of text mining becomes extremely clear, when its applications are introduced.