An Approach to Managing and Organizing Text Documents Using Intelligent Text Analysis

Abstract

Regarding the fact that stored data occupies a large space in organizations and retention systems and information management that has been resulted in gigantic data warehouses, the need for extracting an appropriate model is felt increasingly. Text mining is one of the most significant methods for extracting a useful and appropriate model that helps organizations in achieving their goals through extraction and adaption of knowledge out of data sets. Those methods allow for a new horizon for trading and protecting intellectual property of authors’ works. In this paper, a new approach is needed to decipher the text patterns to organize an intelligent text analysis. The main purpose of the paper is applying a proper method of preserving the works of writers, scholars and text documents. Regarding the number of those works and documentary management systems the size of available data has been increased considerably. In order to uncover the implicit knowledge out of this data with considerable usefulness for users a specific method is required that has been practiced in the data mining field. Much of this available data is unstructured or semi-structured text which one can use it in addition to data mining methods, technologies such as natural language processing, intelligent analysis and Science Statistics used.

Keywords

• Text Search
• Text Management
• Intellectual Property
• Information Extraction
• Data Mining