                                      Shaidah Jusoh 1 and Hejab M. Alfawareh 2 1,2 College of Computer Science & Information Systems, Najran University P.O Box 1988, Najran, Saudi Arabia Abstract Text mining is a very exciting research area as it tries to discover knowledge from unstructured texts. These texts can be found on a computer desktop, intranets and the internet. The aim of this paper is to give an overview of text mining in the contexts of its techniques, application domains and the most challenging issue. The focus is given on fundamentals methods of text mining which include natural language possessing and information extraction. This paper also gives a short review on domains which have employed text mining. The challenging issue in text mining which is caused by the complexity in a natural language is also addressed in this paper. Keywords: -; text mining, information extraction, natural language processing, ambiguity. 1. Introduction In this modern culture, text is the most common vehicle for the formal exchange of information. Although extracting useful information from texts is not an easy task, it is a need of this modern life to have a business intelligent tool which is able to extract useful information as quick as possible and at a low cost. Text mining is a new and exciting research area that tries to take the challenge and produce the intelligence tool. The tool is a text mining system which has the capability to analyze large quantities of natural language text and detects lexical and linguistic usage patterns in an attempt to extract meaningful and useful information [1]. The aim of text mining tools is to be able to answer sophisticated questions and perform text searches with an element of intelligence. Technically, text mining is the use of automated methods for exploiting the enormous amount of knowledge available in text documents. Text Mining represents a step forward from text retrieval. It is a relatively new and vibrant research area which is changing the emphasis in text-based information technologies from the level of retrieval to the level of analysis and exploration. Text mining, sometimes alternately referred to as text data mining, refers generally to the process of deriving high quality information from text. Researchers like [2], [3] and others pointed that text mining is also known as Text Data Mining (TDM) and knowledge Discovery in Textual Databases (KDT). According to [4] the boundaries between data mining and text mining are fuzzy. The difference between regular data mining and text mining is that in text mining, the patterns are extracted from natural language texts rather than from structured databases of facts. Text mining is an interdisciplinary field which draws on information retrieval, data mining, machine learning, statis- tics, and computational linguistics. Preprocessing of document collection (text categorization, information extraction, term extraction), storing the intermediate representations, analysing the intermediate representation using a selected technique such as distribution analysis, clustering, trend analysis, and association rules, and visualizing the results are considered necessary processes in designing and implementing a text mining tool. Among the features of text mining systems/tools are: • a user centric process which leverages analysis technologies and computing power to access valuable information within unstructured text data sources ; • text mining processes are driven by natural language processing and linguistic based algorithm • eliminate the need to manually read unstructured data sources. Research in text mining has been carried out since the mid- 80s when the US academic, Prof Don Swanson, realized that, by combining information slice from seemingly unrelated medical articles, it was possible to deduce new hypotheses [5]. In the early years of text mining research, text mining systems were aimed at information specialists. They typically require a combination of domain and informatics expertise to configure. Today, work on text mining has been carried out by researchers for different various type of domains. The aim of this paper is to give an overview of text mining system. The paper is organized as follows. Section 2 presents fundamental techniques in text mining. Section 3 reviews text mining work which has been conducted for a specific domain. Section 4 addressed the challenging issue in developing a robust text mining. Section presents a summary of the paper. IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 6, No 2, November 2012 ISSN (Online): 1694-0814 www.IJCSI.org 431 Copyright (c) 2012 International Journal of Computer Science Issues. All Rights Reserved.