Construction of Rough graph to handle uncertain pattern from an Information System
This work addresses pattern recognition in uncertain data for researchers in rough set theory and data analysis, but it appears incremental as it builds on existing rough membership functions.
The paper tackled the problem of identifying patterns in uncertain information systems by proposing a new method to construct rough graphs using a rough membership function, exploring their operations and properties.
Rough membership function defines the measurement of relationship between conditional and decision attribute from an Information system. In this paper we propose a new method to construct rough graph through rough membership function $ω_{G}^F(f)$. Rough graph identifies the pattern between the objects with imprecise and uncertain information. We explore the operations and properties of rough graph in various stages of its structure.