Distributed conflict analysis across varying analysis levels based on fuzzy formal contexts

Abstract

Conflict analysis aims to understand the causes of conflicts and identify effective solutions. While existing studies have thoroughly examined conflict information within individual information systems, the conflict analysis across different systems remains underexplored. In this paper, we utilize fuzzy formal concept analysis to investigate conflict analysis in multi-source information. First, conflict information fusion strategies for distributed fuzzy formal contexts are proposed, including object set extension (vertical merging) and attribute set extension (horizontal merging). Second, algorithms for updating conflict analysis results when adjusting analysis levels are introduced, considering the varying conflict analysis levels inherent in multi-source information. Finally, the fusion strategies for conflict analysis results at varying analysis levels are evaluated, and the selection of analysis levels is analyzed to optimize computational efficiency. The experimental results demonstrate that fusing conflict information is significantly more efficient than recalculation, and it allows for the selection of varying analysis levels to balance time consumption and information volume. This work enhances the efficiency of conflict analysis in fuzzy formal contexts, providing practical methods for managing multi-source information and adjusting analysis levels to meet specific requirements.