Project Discription

INTRODUCTION

With the increase in the digital text document a new field of Mining is emerged where the process of fetching knowledge from the unorganized data is done. As the association is develop in the words on the different criteria depend on the requirement. Text mining is not similar in fashion that the possible outcome is already known, so without having the exact outcome from the data it predict the knowledge from it, which is base on the rules or step perform by the process of mining. So information which is of ni use in the processing are removed from the document.Text mining is nothing but a procedure to take out the important facts from the text documents. Selection of data for text mining is always the point of discussion. We can understand this point with an illustration that the process of text categorization comes under text mining because of its analogies but few of them think that text categorization should not link through text mining 

  Proposed Work

Preprocessing is a process used for conversion of document into feature vector. Just like text categorizations the preprocessing also has controversy about its division. The preprocessing is divided into two parts – text preprocessing and document indexing [10].

Text preprocessing is consisting of words which are responsible for lowering the performance of learning models. Those words which are responsible for lowering the performance of learning model are called \noisy” words [6].

The words which are misspelled or the abbreviated word or common word {i.e. \is”,\or”,\ a”} are taken into as noise words. The word does not hold any info which is useful for classification.

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