The complexity of Boolean functions
The complexity of Boolean functions
Three partition refinement algorithms
SIAM Journal on Computing
An implementation of an efficient algorithm for bisimulation equivalence
Science of Computer Programming
Modal logic
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
An efficient algorithm for computing bisimulation equivalence
Theoretical Computer Science
Graph mining: Laws, generators, and algorithms
ACM Computing Surveys (CSUR)
Rough Set Based Social Networking Framework to Retrieve User-Centric Information
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Social Network Reduction Based on Stability
CASON '10 Proceedings of the 2010 International Conference on Computational Aspects of Social Networks
Arrow decision logic for relational information systems
Transactions on Rough Sets V
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In classical rough set theory, objects are partitioned into equivalence classes based on their attribute values, which essentially represent the functional information associated with the objects. Therefore, rough set theory can be viewed as a theory of functional granulation. In contrast, relational information systems (RISs) specify the relationships between objects, instead of their properties. This study presents a rough set analysis of relational structures, which are more general than functional information systems (FISs) and RISs. Unlike classical rough set theory, in which the attribute values of objects fully determine the indiscernibility relation, the rough set analysis of relational structures must account for the relationships between objects. This study considers three important concepts of indiscernibility with respect to relational structures: congruence, bisimulation, and exact equivalence. Using these indiscernibility relations, we investigate rough approximations and knowledge reduction. This study extends the application scope of rough set analysis from table-style information systems to relational structures. This extension is important because relational structures play a crucial role in the processing of complex data, such as graph mining or social network analysis.