A Detailed Study on Aggregation Methods used in Natural Language Interface to Databases (NLIDB)

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General framework of NLP query processing system
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Published: Jun 12, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i6s.6947
Keywords:
Structured Query Language (SQL), Pattern Based Aggregation, Query Based Aggregation, Natural Language Interface (NLI), Natural Language Interfaces to Databases (NLIDB)

Main Article Content

Ashlesha Kolarkar
Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram, Vijayawada.
Sandeep Kumar
Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram, Vijayawada,

Abstract

Historically, databases have been the most crucial issue in the study of information systems, and they constitute an essential part of all information management systems. Since, it complicated due to restricting the number of potential users, particularly non-expert database users who must comprehend the database structure to submit such queries. Natural language interface (NLI), the simplest method to retrieve information, is one possibility for interacting with the database. The transformation of a natural language query into a Structured Query (SQL) in a database is known as a "Natural Language Interface to Database" (NLIDB). This study uses NLIDB to handle the works performed under various aggregations with aggregation functions, a grouping phrase, and a possessing clause. This study carefully examines the numerous systematic aggregation approaches utilized in the NLIDB. This review provides extensive information about the many methods, including query-based, pattern-based, general, keyword-based NLIDB, and grammar-based systems, to extract data for a dissertation from a generic module for use in such systems that support query execution utilizing aggregations.

Article Details

How to Cite
Kolarkar, A. ., & Kumar, S. . (2023). A Detailed Study on Aggregation Methods used in Natural Language Interface to Databases (NLIDB). International Journal on Recent and Innovation Trends in Computing and Communication, 11(6s), 411–418. https://doi.org/10.17762/ijritcc.v11i6s.6947
Issue
Vol. 11 No. 6s (2023): Advances in Computational Modeling and Simulation of Computing Systems
Section
Articles

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