Open AccessQuestion to Query: Converting Human Language to DBMS Query
Author(s) -
Yashvi Thakkar,
Faiz Palwala,
Utsav Vyas,
Kumar Agarwal,
Rajesh Kannan Regunathan
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.b2635.129219
Subject(s) - computer science , query language , rdf query language , query optimization , query by example , query expansion , sargable , information retrieval , object query language , web search query , parsing , natural language processing , web query classification , sentence , data control language , view , artificial intelligence , programming language , search engine , database design
In this paper a method has been proposed keeping in the mind the need for systems that could generate structured queries from normal language keeping in mind that the user has no prior knowledge of database query language. A novel method which aims at aiding analyst who aren’t well versed with codes, but need quantitative outputs to analyze, predict and alert the business or market. A python model is used, which aims at converting any sentence typed in English to a query provided that such tables and database is present for query processing. Tree tagging is used here to relate words typed in to SQL query syntax. Any sentence typed in by analyst, it further annotated by parts of speech and lemmas. A list of generic words and stop words is used while parsing the input the sentence and tagging it. Query is generated by simultaneously removing the stop words, mapping the keywords with the one’s used in structured query language. The generated query comes out in form of a JSON file.