Building Domain Ontologies and Automated Text Categorization: a Contribution to Nlp

In recent years there has been a massive growth in textual information especially in the internet. 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. 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. Text categorization means assigning an uncategorized document into one or more pre-defined categories. So far researches have focused on using word based representation called Bag-of-Words (BOW) with strong statistical users; some are based on complex NLP representation based on words, phrases, sentences,and word-sense. This book focuses on the construction of domain based ontology so that users can relate to different topics of a domain and an automated text categorization technique based on Term Frequency ? Inverse Document Frequency (tf -idf) method is proposed that will categorize the uncategorized documents. With this approach user can not only categorize documents but also visualize the relationship among the terms of the document