DOI:10.20894/IJWT.
Periodicity: Bi Annual.
Impact Factor:
SJIF:4.78 & GIF:0.428
Submission:Any Time
Publisher: IIR Groups
Language: English
Review Process:
Double Blinded
India is the home of different languages, due to its cultural and geographical diversity. The official and regional languages of India play an important role in communication among the people living in the country. In the Constitution of India, a provision is made for each of the Indian states to choose their own official language for communicating at the state level for official purpose. In the eighth schedule as of May 2008, there are 22 official languages in India.The availability of constantly increasing amount of textual data of various Indian regional languages in electronic form has accelerated. So the Classification of text documents based on languages is essential. The objective of the work is the representation and categorization of Indian language text documents using text mining techniques. South Indian language corpus such as Kannada, Tamil and Telugu language corpus, has been created. Several text mining techniques such as naive Bayes classifier, k-Nearest-Neighbor classifier and decision tree for text categorization have been used.There is not much work done in text categorization in Indian languages. Text categorization in Indian languages is challenging as Indian languages are very rich in morphology. In this paper an attempt has been made to categories Indian language text using text mining algorithms
