Abstract: Concept reduction is central to formal concept analysis(FCA),which simplifies concept lattices while preserving all original information.As a combination of three-way decision theory and traditional concept lattices,three-way concept lattices feature distinct reduction requirements.Unlike traditional reduction that only maintains positive information structure,three-way concept reduction demands complete retention of positive,negative and uncertain knowledge under stricter criteria,making it more suitable for multi-dimensional complex decision-making.Since current studies on three-way concept lattice reduction are insufficient and efficient methods are lacking.To address this issue,this paper proposes an OE concept reduction framework based on global relevance and redundancy.The framework integrates the relevance and redundancy analysis of OE concepts to construct an optimized OE concept reduction method,which can effectively identify and eliminate redundant concepts while ensuring the integrity of the three-way knowledge structure,thereby obtaining an OE concept reduction result that preserves binary relations.Experimental results demonstrate that the proposed method significantly outperforms existing OE concept reduction methods in terms of the computational efficiency of reduction,effectively enhancing the processing performance of OE concept reduction.It also provides new support for the theoretical development of OE concept lattices and their application in complex decision analysis.

Key words: Formal contexts, Binary relation, Three-way concept, Concept reduction, Granular computing.