Keyword based Marathi Interface to the Database using Natural Language Processing

A.B. Patil¹ , S.C. Pawar²

1. Dept. of Information Technology , Rajarambapu Institute of Technology, Rajaramnagar, India.
2. Dept. of Computer Engineering, K.J.Somiaya College of Engineering, Mumbai, India.

Correspondence should be addressed to: ashwini.patil@ritindia.edu.

Section:Research Paper, Product Type: Isroset-Journal
Vol.6 , Issue.1 , pp.50-55, Feb-2018

CrossRef-DOI:   https://doi.org/10.26438/ijsrcse/v6i1.5055

Online published on Feb 28, 2018

Copyright © A.B. Patil, S.C. Pawar . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Now a day’s a computer plays a vital role in almost all the sectors/application. The available information is stored and retrieved in/from the database. Database Management system (such as SQL, Oracle) allows to handle the database by creation of the database, querying the database, updating database, and administration of databases. So there is need of skilled person (database experts) in order to deal with database management system, but this is not always true. The common people with lack of expertise are there to handle the database, who doesn’t know about the syntax/format of queries to be fire on the database. Also they are more comfortable in their native languages like “Marathi”, “Hindi”, “Arabic”. It is essential to have the database interface in native language (e.g Marathi) so that the non-expert person can also interact with database for storing and extracting the data. In this paper we are proposing the Marathi language interface using Natural Language Processing (NLP) to handle the database. This interface can handle the queries in native language which may be syntactically and semantically incorrect and convert it into correct form.(e.g SQL query). Rest of the paper is organized as follows, Section I contains the introduction of natural language processing , Section II contain the related work of natural language interface to the database system, Section III contain the problem definition and proposed system, Section IV contain the architecture and algorithm of proposed system, section V explain the working of proposed system with example, Section VI give conclusion with future direction.

Key-Words / Index Term :
Natural Language Processing, SQL, Keyword based interface, Natural language interface

References :
[1] W. Woods, R. Kaplan,“The lunar sciences natural language information system: final report” Published in 1978.
[2] B.Sujatha, Dr.S.Viswanadha Raju and H. Shaziya , “A Survey of Natural Language Interface to Database Management System” International Journal of Science and Advanced Technology (ISSN 2221-8386) Volume 2 No 6 June 2012.
[3] E. D. Sacerdoti , “Language Access to Distributed Data with Error Recovery”
[4] H. D. David Warren and Fernando C. N. Pereira, “An Efficient Easily Adaptable System for Interpreting Natural Language Queries” American Journal of Computational Linguistics, volume 8, Number 3-4, July-December 1982
[5] A.Shah, Dr. J. Pareek, H. Patel and N. Panchal , “NLKBIDB - Natural Language and Keyword Based Interface to Database” , 978-1-4673-6217-7/13 ,2013 IEEE
[6] F.Siasar, M.Norouzifard1, S.H.Davarpanah2, M.H. “Using Natural Language Processing in Order to Create SQL Queries” Proceedings of the International Conference on Computer and Communication Engineering at Kuala Lumpur, Malaysia,
[7] M. Dua, S. Kumar, Z. Singh Virk, “Hindi Language Graphical User Interface to Database Management System” , 12th International conference on Machine Learning and Application, 2013.
[8] Prof. A. Shingala and Dr. P. Virparia, “Enhancing the Relevance of Information Retrieval by Querying the Database in Natural form” , International Conference on Intelligent Systems and Signal Processing (ISSP),2013