Data modeling and querying with fuzzy sets: A systematic survey

Uncertainty extensively exists in data and knowledge intensive applications, in which fuzzy information processing plays a crucial role. Fuzzy sets have been extensively used to enhance various database models for managing fuzzy data or flexibly querying crisp data. This has resulted in numerous contributions in this research area. This paper pays attention to three crucial issues in fuzzy techniques for data management: modeling fuzzy data, querying fuzzy data, and fuzzy queries over crisp data, and provides a full up-to-date survey on the current state of the art in fuzzy data modeling and querying. The paper identifies fuzzy conceptual data models, fuzzy (relational and object-oriented) database models and fuzzy XML model as well as the relationships among these fuzzy data models. For each type of fuzzy data models, the paper summarizes its query processing. The paper also reviews fuzzy querying over classical data models. In addition to providing a generic overview of the approaches for fuzzy data modeling and querying, this survey paper serves for identifying possible research opportunities in the area of fuzzy data processing.(c) 2022 Elsevier B.V. All rights reserved.

Automated summary

This paper provides a comprehensive survey on the current state of the art in fuzzy data modeling and querying. It focuses on three crucial issues in fuzzy techniques for data management: modeling fuzzy data, querying fuzzy data, and fuzzy queries over crisp data. The paper identifies different fuzzy data models and summarizes their query processing. It also reviews fuzzy querying over classical data models.