Gagandeep Kaur
Computer Science and Engineering Department, Symbiosis Institute of Technology, Nagpur Campus, Symbiosis International (Deemed University), Pune, Maharashtra, India.

Poorva Agrawal
Computer Science and Engineering Department, Symbiosis Institute of Technology, Nagpur Campus, Symbiosis International (Deemed University), Pune, Maharashtra, India.

Hemlata Shelar
Senior Software Developer, IBM Cloud, Bangalore, India.

Gebrehiwot Teklehaymanot Abraha
Computer Science and Engineering Department, Aksum University, Aksum, Ethiopia.

DOI https://doi.org/10.33889/IJMEMS.2024.9.4.048

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Abstract

The amount of data being produced and used every day is increasing rapidly. Different operations are performed on the data that is stored in database systems to generate meaningful information. The task of retrieving data from the database is difficult for inexperienced users who don’t have great knowledge of Database Management System (DBMS) languages such as Structured Query Language (SQL). Using Natural Language Processing, anyone can directly interact with the database system. To achieve this type of communication, we have developed a novel and improved Intelligent Search Engine (ISE) Tool using natural language processing. Using this search engine, the user can query the database system in natural language (human-understandable language). The intelligent search engine will convert the natural language query into the DBMS language query to retrieve the data from the database. The proposed system also has a query recommendation engine that recommends the possible queries in case of any error or if the result is not found. The intelligent search engine proposed in this work is a generic tool that is not dependent on the front or back end of the system, therefore it can be used for any database system.

Keywords- Natural language processing, Query autocompletion, Named entity recognition, Text categorization, Term frequency- inverse document frequency (TF-IDF).

Citation

Kaur, G., Agrawal, P., Shelar, H., & Abraha, G. T (2024). Intelligent Search Engine Tool for Querying Database Systems. International Journal of Mathematical, Engineering and Management Sciences, 9(4), 914-930. https://doi.org/10.33889/IJMEMS.2024.9.4.048.