Abstract
The amount of data present online is growing very rapidly, hence a need for organizing and categorizing data has become an obvious need. The Information Retrieval (IR) techniques act as an aid in assisting users in obtaining relevant information. IR in the Indian context is very relevant as there are several blogs, news publications in Indian languages present online. This work looks at the suitability of Naive Bayesian methods for paragraph level text classification in the Kannada language. The Naive Bayesian methods are the most primitive algorithms for Text Categorization tasks. We apply dimensionality reduction technique using Minimum term frequency, stop word identification and elimination methods for achieving the task. It is evident that Naive Bayesian Multinomial model outperforms simple Naive Bayesian approach in paragraph classification tasks .
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Artificial Intelligence & Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
