Text mining: An improvised feature based model approach

In this knowledge era, plethora of textual information is growing rapidly which is usually semistructured or unstructured data collected and stored in various databases. Discovery of knowledge from this available database is not simple. Thus, the automatic feature selection approach is very much necessary in the processing of this unstructured data. The Feature selection approach focuses towards processing unstructured information into relevant information, helps to understand and visualize the data, it also reduces the training and processing time of huge amounts of data. Feature helps in caarying out the text mining task effectively and accurately. Text mining offers various methods to fetch the interested data from vast databases. Feature selection proves to have a vital role in this process. In this paper, bread model is proposed that processes text document using the input termset. Based on first principles of instruction application methodology, the model phases are implemented that provides the effective results.