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Manual Analysis of huge amount of textual data requires a treme ndous amount of processing time and effort in reading the text and organizing them in required format. In the current scenario, the major problem is with text categorization because of the high dimensionality of feature space. Now -a-days there are many methods available to deal with text feature selection. This paper aims atsuch semi automated text categorization feature selection methodology to deal with a massive data using one of the phases of David Merrills First principles of instruction (FPI ). It uses a pre-defined category group by providing them with the proper training set based on the demonstration phase of FPI. The methodology involves the text tokenization, text categorization and text analysis.

Semi Automated Text Categorization using Demonstration Based Term Set