TAILIEUCHUNG - Preprocessing techniques for text mining - an overview
This paper discussed about the text mining and its preprocessing techniques. Text mining is the process of mining the useful information from the text documents. It is also called knowledge discovery in text (KDT) or knowledge of intelligent text analysis. | ISSN:2249-5789 et al , International Journal of Computer Science & Communication Networks,Vol 5(1),7-16 Preprocessing Techniques for Text Mining - An Overview Dr. S. Vijayarani1, Ms. J. Ilamathi2, Ms. Nithya3 Assistant Professor1, M. Phil Research Scholar2, 3 Department of Computer Science, School of Computer Science and Engineering, Bharathiar University, Coimbatore, Tamilnadu, India1, 2, 3 Abstract Data mining is used for finding the useful information from the large amount of data. Data mining techniques are used to implement and solve different types of research problems. The research related areas in data mining are text mining, web mining, image mining, sequential pattern mining, spatial mining, medical mining, multimedia mining, structure mining and graph mining. This paper discussed about the text mining and its preprocessing techniques. Text mining is the process of mining the useful information from the text documents. It is also called knowledge discovery in text (KDT) or knowledge of intelligent text analysis. Text mining is a technique which extracts information from both structured and unstructured data and also finding patterns. Text mining techniques are used in various types of research domains like natural language processing, information retrieval, text classification and text clustering. Keywords: Text mining, Stemming, Stop words elimination, TF/IDF algorithms, Word Net, Word Disambiguation. unstructured or semi-structured data sets such as emails HTML files and full text documents etc. [1]. Text Mining is used for finding the new, previously unidentified information from different written resources. Structured data is data that resides in a fixed field within a record or file. This data is contained in relational database and spreadsheets. The unstructured data usually refers to information that does not reside in a traditional row-column database and it is the opposite of structured data. SemiStructured data is the data .
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