Data compression of dynamic set-valued information systems

TL;DR

This paper introduces new tolerance relations for set-valued information systems and proposes a data compression method for attribute reductions, simplifying the analysis of dynamic systems with illustrative examples.

Contribution

The paper presents novel tolerance relations and a data compression approach for attribute reduction in dynamic set-valued information systems, enhancing efficiency.

Findings

Tolerance relations have specific properties for set-valued systems

Data compression significantly simplifies attribute reduction

Illustrative examples demonstrate the effectiveness of the approach

Abstract

This paper further investigates the set-valued information system. First, we bring forward three tolerance relations for set-valued information systems and explore their basic properties in detail. Then the data compression is investigated for attribute reductions of set-valued information systems. Afterwards, we discuss the data compression of dynamic set-valued information systems by utilizing the precious compression of the original systems. Several illustrative examples are employed to show that attribute reductions of set-valued information systems can be simplified significantly by our proposed approach.