© 2016. Swapna Narala, B. Padmaja Rani & K. Ramakrishna. This is a research/review paper, distributed under the terms of the Creative Commons Attribution-Noncommercial 3.0 Unported License http://creative commons. org/licenses/by-nc/3.0/), permitting all non-commercial use, distribution, and reproduction inany medium, provided the original work is properly cited. Telugu Text Categorization using Language Models By Swapna Narala, B. Padmaja Rani & K. Ramakrishna JNTU College of Engineering Abstract- Document categorization has become an emerging technique in the field of research due to the abundance of documents available in digital form. In this paper we propose language dependent and independent models applicable to categorization of Telugu documents. India is a multilingual country; a provision is made for each of the Indian states to choose their own authorized language for communicating at the state level for legitimate purpose. The availability of constantly increasing amount of textual data of various Indian regional languages in electronic form has accelerated. Hence, the Classification of text documents based on languages is crucial. Telugu is the third most spoken language in India and one of the fifteen most spoken language n the world. It is the official language of the states of Telangana and Andhra Pradesh. A variant of k-nearest neighbors algorithm used for categorization process. The results obtained by the Comparisons of language dependent and independent models. Keywords: text categorization, language dependent and independent models, k-nearest neighbors. GJCST-H Classification: D.2.11,D.2.12 TeluguTextCategorizationusingLanguageModels Strictly as per the compliance and regulations of: Online ISSN: 0975-4172 & Print ISSN: 0975-4350 Publisher: Global Journals Inc. (USA) Type: Double Blind Peer Reviewed International Research Journal Volume 16 Issue 4 Version 1.0 Year 2016 Information & Technology Global Journal of Computer Science and Technology: H