Component similarity based conflict analysis: An information fusion viewpoint

Conflict is ubiquitous in social life. In many cases, conflict analysis based on single-valued information systems is no longer valid, such as TCM diagnosis. To this end, we model this problem as component similarity based conflict analysis. Specifically, we put forward a type of three-way n-valued concept lattices to handle set-valued formal contexts, based on which conflict analysis is performed by considering component similarity. What is more, a method from an information fusion viewpoint is proposed to realize fast conflict analysis. Finally, experimental results verify that the information fusion based conflict analysis method can greatly reduce time consumption in most occasions due to the fact that it produces less concepts with less time, and spends less time on visiting the concept space to determine the conflict states. This work will bring a novel idea to the component similarity based distributed big data analysis.

Automated summary

This article addresses the issue that conflict analysis based on single-valued information systems is no longer valid. It proposes a conflict analysis method based on component similarity, which uses three-way n-valued concept lattices to handle set-valued formal contexts and realizes fast conflict analysis from an information fusion viewpoint. Experimental results verify the effectiveness of this method in reducing time consumption.