Paper Title
Formulating SQL Queries from Natural Language Processing for Students Using Mobile Learning
Article Identifiers
Registration ID: IJNRD_200294
Published ID: IJNRD2307102
DOI: https://doi.org/10.5281/zenodo.8150058
Authors
Parth Mody , Maanaav Motiramani , Param Sejpal , Abhitay Shinde
Keywords
Natural Language Processing (NLP), Structured Query Language (SQL), CSV, Tokenization, POS tagging, Chunking, Parsing, Featured context free language, Speech to Text, Mobile Learning, User Experience, Data retrieval.
Abstract
Mobile learning opens new worlds of information and personal development. To enable more personalized learning via mobile devices, several clever approaches should be implemented into mobile-assisted learning systems. This paper examines and explores several systems created with natural language processing (NLP) to extract relevant information from a database by utilizing structured natural language questions as input and SQL queries as output. Natural Language Processing (NLP) tools can be used to evaluate students' flaws throughout the mobile learning assessment process. Furthermore, the approach broadens its use beyond student learning by incorporating CSV data retrieval capabilities. Users, such as placement cell workers dealing with student databases, can perform natural language searches to retrieve useful information from CSV files. The design of the proposed model includes a user interface for submitting English inquiries, followed by NLP modules for analyzing the queries and mapping them to SQL queries. The SQL queries may then be run to obtain the necessary data from the database. It illustrates the power of natural language processing techniques in supporting mobile learning and enhancing data retrieval operations.
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How To Cite (APA)
Parth Mody, Maanaav Motiramani, Param Sejpal, & Abhitay Shinde (July-2023). Formulating SQL Queries from Natural Language Processing for Students Using Mobile Learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(7), b1-b7. https://doi.org/10.5281/zenodo.8150058
Issue
Volume 8 Issue 7, July-2023
Pages : b1-b7
Other Publication Details
Paper Reg. ID: IJNRD_200294
Published Paper Id: IJNRD2307102
Downloads: 000121983
Research Area: Science & Technology
Country: Mumbai, Maharashtra, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2307102.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2307102
Crossref DOI: https://doi.org/10.5281/zenodo.8150058
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This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition


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