Proposing a Model for Extracting Information from Textual Documents, Based on Text Mining in E-learning

As computer networks become the backbones of science and economy، enormous quantities documents become available. So، for extracting useful information from textual data، text mining techniques have been used. Text Mining has become an important research area that discoveries unknown information، facts or new hypotheses by automatically extracting information from different written documents. Text mining aims at disclosing the concealed information by means of methods which on the one hand are able to cope with the large number of words and structures in natural language and on the other hand allow handling vagueness، uncertainty and fuzziness. Text mining، referred to as text data mining، roughly equivalent to text analytics، refers to the process of deriving high-quality information from text that high-quality information is typically derived through the patterns and processes. Moreover، text mining، also known as text data mining or knowledge discovery from textual databases، refers to the process of extracting patterns or knowledge from text documents. In this research، a survey of text mining techniques and applications in e-learning has been presented. During these studies، relevant researches in the field of e-learning were classified. After classification of researches، related problems and solutions were extracted. In this paper، first، definition of text mining is presented. Then، the process of text mining and its applications in e-learning domain are described. Furthermore، text mining techniques are introduced، and each of these methods in the field of e-learning is considered. Finally، a model for the information extraction by text mining techniques in e-learning domain is proposed.