Paper Title
An Expert System Model That Enables the Development of Institutional Knowledge Using Text Mining Methods in Open Source Software

Abstract
With the rapidly developing information technology, institutions store the most important data in digital storage. This information is the most important data sources to create the company's institutional knowledge. All information obtained by the Company is the company's know-how. There are many workflow process such as reducing the cost, improving the quality of products and services offered by the company, ensure the efficiency, satisfying the expectations and demands of customers. There are several open source applications to manage each of these workflow processes and these applications produce qualitative or quantitative data. Management of big data which increases with growth of the company is quite difficult. This may cause false recognition of the important knowledge which is hidden in big data while data analysis and reporting. Text mining methods can be used for the analysis which is extremely important in order to increase the enterprise business intelligence of these data. In this study, A model is suggested to generate useful knowledge in big data which created by open source applications with text mining methods such as classification, association analysis, feature extraction and clustering. Keywords- Big Data, Text Mining, Expert Systems, Open Source Software, Institutional Knowledge.