Survey on Pre Processing Techniques for Text Mining
Data Mining is a versatile sublet in the field of computer science. It is the computational evolution mode of detecting patterns in large data sets. This paper give an indication on the different pre processing techniques to mine text data. Text mining applications include Information Retrieval, Information Extraction, Categorization, and Natural Language Processing. The pre processing of text mining starts with Tokenization, followed by Stop word removal and finally stemming. This paper evaluates Porter's and Krovetz algorithm, highlighting their applications and drawbacks.