Published Paper Details:

The huge amount of data continuously generated in the world every day and it is a very difficult task of extracting meaningful information from a large amount of data, fetching meaningful information from raw data is challenging task. Data mining is done basically for fetching valuable information from a large amount of data. There are numerous research fields related to data mining are text mining, web mining, sequential pattern mining, medical mining, multimedia mining, structural mining, and graph mining. Text mining nowadays very emerging research area, it is the process of mining meaningful and valuable information from a textual document. Preprocessing is the crucial step in text mining or data mining. Preprocessing of raw data includes removal of missing values and discretization. Missing values can be handled by replacing missing value technique and by deletion method. Discretization responsible for converting continuous attributes into intervals and relating each interval with some specific data value and it is handled by the binning method like equal width binning, equal frequency binning and by entropy-based discretization method. It may be supervised or unsupervised but doing discretization sometimes responsible for the loss of information.