Text mining: Concepts and methods

nowadays, a huge amount of available information on the web is text documents and articles. Text mining is a way to extract unstructured and semi-structured information from this available information on the Internet and Also, mining process of the text of knowledge and unknown, incomprehensible and potential patterns among the multitude of datasets. This research is a type of library studies. Although text mining methods are mostly based on Latin sources, but by searching Persian databases, we have found over the past decade, the subject of text mining has become doubly important for Iranian researchers, especially students of computer science and information technology; So that a significant part of the conference papers related to computer science and technology are articles related to this field. Research findings show that text mining is an application of data mining and the main difference between them is : the extraction of patterns from text with natural language in text mining, while data mining operates on structured databases. Text mining processes have two main phases: document preprocessing and knowledge extraction. So far, eight techniques have been introduced for text mining which are: Information extraction, information retrieval, text summarization, classification, clustering, visualization, natural language processing and belief mining. In recent years, much attention has been paid to text mining in the international and national spheres. The dramatic increase in textual data has prompted researchers to look for ways to explore this data. Naturally, Iranian researchers have been no exception. Text mining, with all its methods and techniques, is an effort to assist researchers in extracting useful and valuable knowledge and information from the mass of unstructured texts scattered throughout the Internet.