Domain Based Ontology and Automated Text Categorization Based on Improved Term Frequency – Inverse Document Frequency

Abstract — In recent years there has been a massive growth in textual information in textual information especially in the internet. People now tend to read more e-books than hard copies of the books. While searching for some topic especially some new topic in the internet it will be easier if someone knows the pre-requisites and post- requisites of that topic. It will be easier for someone searching a new topic. Often the topics are found without any proper title and it becomes difficult later on to find which document was for which topic. A text categorization method can provide solution to this problem. In this paper domain based ontology is created so that users can relate to different topics of a domain and an automated text categorization technique is proposed that will categorize the uncategorized documents. The proposed idea is based on Term Frequency – Inverse Document Frequency (tf-idf) method and a dependency graph is also provided in the domain based ontology so that the users can visualize the relations among the terms. Index Terms—Term Frequency – Inverse Documen