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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
About the author
Sukanya Ray is currently associated with a U.S.A based software firm as a developer in 4G LTE technology. She is M.Tech in Computer Science and Engineering from Amity School of Engineering & Technology, Noida affiliated to Amity University. Her research interest includes Natural Language Processing, MANET and wireless sensor network
