F10080486S419

Development of Reading Comprehension System for Kannada Text Documents
Anagha Vembar¹, DivyaTantri², Akshita Saxena³, Abhishek Narayanan⁴, Jagadish S Kallimani⁵

¹Anagha Vembar, Department of Computer Science and Engineering, M S Ramaiah Institute of Technology, Bangalore, India.

²Divya Tantri, Department of Computer Science and Engineering, M S Ramaiah Institute of Technology, Bangalore, India.

³Akshita Saxena, Department of Computer Science and Engineering, M S Ramaiah Institute of Technology, Bangalore, India.

⁴Abhishek Narayanan, Department of Computer Science and Engineering, M S Ramaiah Institute of Technology, Bangalore, India. 

⁵Jagadish S Kallimani, Department of Computer Science and Engineering, M S Ramaiah Institute of Technology, Bangalore, India. 

Manuscript received on 05 April 2019 | Revised Manuscript received on 12 April 2019 | Manuscript Published on 26 July 2019 | PP: 42-45 | Volume-8 Issue-6S4 April 2019 | Retrieval Number: F10080486S419/19©BEIESP | DOI: 10.35940/ijitee.F1008.0486S419

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Abstract: Reading Comprehension (RC) plays an important role in Natural Language Processing (NLP) as it reads and understands text written in Natural Language. Reading Comprehension systems comprehend the given document and answer questions in the context of the given document. This paper proposes a Reading Comprehension System for Kannada documents. The RC system analyses text in the Kannada script and allows users to pose questions to It in Kannada. This system is aimed at masses whose primary language is Kannada – who would otherwise have difficulties in parsing through vast Kannada documents for the information they require. This paper discusses the proposed model built using Term Frequency – Inverse Document Frequency (TF-IDF) and its performance in extracting the answers from the context document. The proposed model captures the grammatical structure of Kannada to provide the most accurate answers to the user.

Keywords: Reading Comprehension, Natural Language Processing, Kannada, Term Frequency- Inverse Document Frequency, Answer Extraction.
Scope of the Article: Computer Science and Its Applications