IJCSIS Papers by tamunoemi nwachukwu
IJCSIS Vol 18 No. 4 April 2020 Issue, 2020
This Natural Language query is a request that is issued in the normal language that humans are co... more This Natural Language query is a request that is issued in the normal language that humans are comfortable with. Every day, technologies for information retrieval and storage are emerging. Natural Language Processing (NLP) is one of the fast rising technologies which make the Human-Computer-Interaction easier. With the aid of this technology, users can query a database using natural and convenient language and the system should be able to give an intelligent and accurate answer. Several NL to SQL conversion Models are currently in use for the conversion of queries issued in the natural language, yet there remains the problem of inefficient translation due to restricted keyword vocabulary or knowledge base with those models due to the use of poorly formed dataset used to implement these models. In this work, enhanced Keyword-based conversion models which will eliminate the inefficiencies of the existing systems have been developed, and produced conversion accuracy Using Keyword-based approach. Tools such as POS tagger, NLTK tool are used to translate the natural language query in form of text or speech to SQL query and then display the result in a user-friendly interface for the users to access. We adopted the Structured System Analysis and Design Methodology (SSADM) for this approach. The system was implemented using Hypertext Preprocessor (PHP), JavaScript and MySQL as the Backend. The result shows that accurate conversions can now be made using well prepared datasets. This work will be beneficial to workers that interface with data in an academic environment and naïve people in different communities such as the economics, and every other person that interfaces with data stored in the database.
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IJCSIS Papers by tamunoemi nwachukwu