Abstract
Writing SQL queries for database is a complex and skill requiring task especially for the new users. The situation becomes more critical when a low skilled person want to access and analyze his data from a relational database. These scenarios require expertise and skills in terms of understanding and writing the accurate and functional queries. However, these complex tasks can be simplified by providing an easy interface to the users. In order to resolve all such issues, automated software tool is needed, which facilitates both users and software engineers. In this paper we present a novel approach with name Que-Gen (Query Generator) that generates SQL queries based on the specification provided in National English Language. Users need to write the requirements in simple English in a few statements. After a semantic analysis and mapping of the associated information. Que-Gen generates the intended SQL queries that can be executed directly on the database. An experimental study has been conducted to analyze the performance and the accuracy of the purposed tool.
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References
Li, Y., Yang, H., Jagadish, H.V.: Constructing a generic natural language interface for an XML database. In: Ioannidis, Y., et al. (eds.) EDBT 2006. LNCS, vol. 3896, pp. 737–754. Springer, Heidelberg (2006). https://doi.org/10.1007/11687238_44
Li, Y., Yang, H., Jagadish, H.V.: NaLIX: an interactive natural language interface for querying XML. In: SIGMOD (2005)
Popescu, A.-M., Etzioni, O., Kautz, H.: Towards a theory of natural language interfaces to databases. In: IUI, pp. 149–157 (2003)
Popescu, A.-M., Armanasu, A., Etzioni, O., Ko, D., Yates, A.: Modern natural language interfaces to databases: composing statistical parsing with semantic tractability. In: COLING (2004)
Wong, Y.W.: Learning for semantic parsing using statistical machine translation techniques. Technical report UT-AI-05- 323, University of Texas at Austin, Artificial Intelligence Lab, October 2005
Satav, A.G., Ausekar, A.B., Bihani, R.M., Shaikh, A.: A proposed natural language query processing system. Int. J. Sci. Appl. Inf. Technol. 3(2) (2014)
Kaur, G.: Usage of regular expressions in NLP. IJRET 3(1), 7 (2014)
Gaikwad, M.P.: Natural language interface to database. IJEIT 2(8) (2013)
Kaur, J., Chauhan, B., Korepal, J.K.: Implementation of query processor using automata and natural language processing. Int. J. Sci. Res. Publ. 3(5) (2013)
Bhadgale, A.M., Gavas, S.R., Patil, M.M., Pinki, R.: Natural language to SQL conversion system. IJCSEITR 3(2), 161–166 (2013). ISSN 2249-6831
Agrawal, A.J., Kakde, O.G.: Semantic analysis of natural language queries using domain ontology for information access from database. IJISA 12, 81–90 (2013)
Kaur, S., Bali, R.S.: SQL generation and execution from natural language processing. Int. J. Comput. Bus. Res. (2012). ISSN (Online): 2229–6166
Deshpandel, A.K., Prakash, R.: Natural language processing using probabilistic context free grammar. Int. J. Adv. Eng. Technol. 3(2), 568–573 (2012). Devale, Department of Information Technology, Bharati Vidyapeeth Deemed University, Pune, India
Tamrakar, A., Dubey, D.: Query optimization using natural language processing. IJCST 3(1) (2012). Department of CSE, Chhatrapati Sivaji Institute of Technology, CG, India
Gage, M.: A Survey of “Natural Language Processing Techniques for the Simplification of User Interaction with Relational Database Management Systems”. California Polytechnic State University, San Luis Obispo (2012)
Nihalani, N., Silakari, S., Motwani, M.: “Natural language Interface for database”: a brief review. IJCSI 8(2) (2011)
Giordani, A., Moschitti, A.: Semantic mapping between natural language questions and SQL queries via syntactic pairing. Department of Computer Science and Engineering University of Trento via Sommarive 14, 38100 POVO (TN) – Italy (2010)
Chaudhry, G.R.S., KulKarni, N.: Natural language processing using semantic grammar. IJCSE 2(2), 219–223 (2010)
Karande, N.D., Patil, G.A.: Natural language database interface for selection of data using grammar and parsing. World Acad. Sci. Eng. Technol. 3, 11–26 (2009)
Patil, R., Chen, Z.: STRUCT: “Incorporating contextual information for english query search on relational databases” (2012)
Naeem, M.A., et al.: QueGen: “Natural language interface for data warehouse” (2012)
Shannon, K.J.: Implementation of natural language to structured query language translator (2011)
Androutsopoulos, I., et al.: Interfacing the natural language to front end to relational database (1995)
Knowles, S.: SQL-TUTOR intelligent tutoring system (1999)
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Khan, S.S., Saeed, A., Majeed, Y., Kamran, M. (2019). Natural Language Based SQL Query Verification Against Relational Schema. In: Bajwa, I., Kamareddine, F., Costa, A. (eds) Intelligent Technologies and Applications. INTAP 2018. Communications in Computer and Information Science, vol 932. Springer, Singapore. https://doi.org/10.1007/978-981-13-6052-7_34
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DOI: https://doi.org/10.1007/978-981-13-6052-7_34
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