A fuzzy logic‐based approach for fuzzy queries over NoSQL graph database

Abstract

The massive production of data in the web environment increases the need for efficient and effective solutions to store and manage data. NoSQL databases with the capability of storing various types of data were introduced to be used in the management of big data. Besides, supporting flexible querying has significant impacts on data management usability and users prefer to ask their requests using fuzzy terms and get crisp results to make efficient decisions. In this paper, a fuzzy‐based approach is presented which adopts fuzzy queries and delivers crisp recommendations to the users. For this purpose, a counselor, which acts as a fuzzy agent and has knowledge about the data, defines fuzzy terms, membership functions and fuzzy rule tables in a way that each user can ask queries through fuzzy terms. The evaluation results show the efficiency of the proposed approach which removes the need for high‐level programming skills for users. As a result, our approach's efficiency and user acceptance are increased as well and made it an appropriate solution for using ambiguous queries in big graph databases.

ERMer: a serverless platform for navigating, analyzing, and visualizingEscherichia coliregulatory landscape through graph database

“…This idea is not new, but has now become more viable via the introduction of scalable graph databases ( 2 ). Unlike traditional ways of managing data, such as relational databases, graph modelling allows for the real-world heterogeneity of data and efficiently handles complex deep queries ( 2 , 3 ). Graph databases have been widely adopted, particularly in areas including complex relationships such as social networks, financial services, and marketing ( 4 , 5 ).…”