UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 8 Issue 6
June-2021
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2106077


Registration ID:
310139

Page Number

a592-a597

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Title

NATURAL LANGUAGE TO SQL CONVERSION USING DEEP LEARNING(LSTM) & NLP

Abstract

In today's world, large amounts of data are produced within a fraction of seconds. Data can be structured, unstructured and semi-structured. The proposed system focused on structured data handling in a simpler way. The RDBMS uses SQL to perform actions like search, edit, remove and add records to the database. People who are unaware about SQL find it difficult to do these tasks. This system helps such people without wasting time on learning SQL. The main objective is to handle more number queries and effective query formulation using ML Techniques like LSTM. The English language question to equivalent SQL Query formation is done using NLP, LSTM and self-made algorithms for basic AI processing. Due to this architecture, the system handles select, delete, create queries along with various conditions like order by, group by, foreign key, aggregate functions, relation operations, distinct clause. The queries are tested on the SQlite database. The overall accuracy of query generation for six tables is 86.3%

Key Words

DBMS, NLP, LSTM, POS, CNN, RDBMS

Cite This Article

"NATURAL LANGUAGE TO SQL CONVERSION USING DEEP LEARNING(LSTM) & NLP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.a592-a597, June-2021, Available :http://www.jetir.org/papers/JETIR2106077.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"NATURAL LANGUAGE TO SQL CONVERSION USING DEEP LEARNING(LSTM) & NLP", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppa592-a597, June-2021, Available at : http://www.jetir.org/papers/JETIR2106077.pdf

Publication Details

Published Paper ID: JETIR2106077
Registration ID: 310139
Published In: Volume 8 | Issue 6 | Year June-2021
DOI (Digital Object Identifier):
Page No: a592-a597
Country: Pune, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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