Paper Details: Downloads: 2254
Serial Number: P1121716566
Title: Automatic Conversion of Natural Language into Relational Database Queries
Authors: Prof. Kamal ElDahshan and Khalid Walid and Mennatullah Walid and Mohamed Ali
Abstract: This paper presents possible solutions for a problem faced by casual users in technology fields. This problem is the extraction of information as experienced users through writing queries. The main idea of the project is to convert the user’s natural language to SQL (structured query language) queries. This is done by applying an algorithm to extract the required data from user’s input and then applying the query to the database to extract the needed information. This should be most effective in case of ad-hoc queries. The main goal of the project is to enable the non-specialized user to extract whatever information he needs from the database. As long as the user requires privileges by adding a layer that improves the HCI (human computer interaction) through the use of NLP (natural language processing). This technique eases the extraction of information from the database and lessens the stress and pressure on specialized users, thus increasing the overall efficiency.
Keywords: SQL; NLP; Dependency parsing; Parts of speech tagging; Natural language bank; Data dictionary.
Journal/Conference: International Journal of Artificial Intelligence and Machine Learning
Volume: 14
Issue: 1
Submission Date: 4/16/2017 12:00:00 AM
Review Date: 5/4/2017 12:00:00 AM
Publishing Date: 6/29/2017 12:00:00 AM
Article Downloads: 2254
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