Conflict Analysis in Multi-source Uncertain Environments Based on Three-way Concept Analysis

Authors

  • Tiantian Wang

DOI:

https://doi.org/10.54097/5f17ev69

Keywords:

Conflict Analysis; Multi-Source Information; Uncertain Attitudes; Three-Way Concept Analysis

Abstract

Multiple sources use different attitude to the same agent and issue, which may introduce complex interpretation of agreement and conflict. This paper proposes a framework for complete, aligned evaluations on a common opposition-to-support scale. we use the minimum and maximum accepted evaluations form the source data. A definite attitude is assigned only when all source satisfies that the corresponding support or opposition threshold, and all other evaluations keep unresolved. The result construct a three-valued context and it is analyzed using conflict-oriented three-way concepts. The generated concept intents represent the agreement, confirmed conflict, and boundary issues, while the extents preserve these issue sets. The elementary properties of normalized proportions describe the effects of group enlargement, source addition, and nested threshold changes. Two case studies illustrate the role of the closure, and explain the distinction between reduced conflict and increased information. An arithmetic-mean comparison clarifies the different confirmation policies. The paper provides an interpretable description under three-valued formal context, it provides a solution for conflict analysis of multi-source information.

References

[1] Pawlak, Z. (1998). An inquiry into anatomy of conflicts. Information Sciences, 109, 65–78. https://doi.org/10.1016/S0020-0255(97)10072-X

[2] Yao, Y. (2019). Three-way conflict analysis: Reformulations and extensions of the Pawlak model. Knowledge-Based Systems, 180, 26–37. https://doi.org/10.1016/j.knosys.2019.05.016

[3] Lang, G., Luo, J., & Yao, Y. (2020). Three-way conflict analysis: A unification of models based on rough sets and formal concept analysis. Knowledge-Based Systems, 194, 105556. https://doi.org/10.1016/j.knosys.2020.105556

[4] Ganter, B., & Wille, R. (1999). Formal concept analysis: Mathematical foundations. Springer. https://doi.org/10.1007/978-3-642-59830-2

[5] Qi, J., Wei, L., & Yao, Y. (2014). Three-way formal concept analysis. In Rough sets and knowledge technology (pp. 732–741). Lecture Notes in Computer Science, 8818. Springer. https://doi.org/10.1007/978-3-319-11740-9_67

[6] Zhi, H., Qi, J., Qian, T., & Ren, R. (2020). Conflict analysis under one-vote veto based on approximate three-way concept lattice. Information Sciences, 516, 316–330. https://doi.org/10.1016/j.ins.2019.12.065

[7] Lang, G., & Yao, Y. (2023). Formal concept analysis perspectives on three-way conflict analysis. International Journal of Approximate Reasoning, 152, 160–182. https://doi.org/10.1016/j.ijar.2022.10.014

[8] Zhi, H., Qi, Z., & Li, Y. (2024). An efficient conflict analysis method based on splitting and merging of formal contexts. Information Sciences, 661, 120154. https://doi.org/10.1016/j.ins.2024.120154

[9] Zhi, H., Li, J., & Li, Y. (2022). Multi-level conflict analysis based on fuzzy formal contexts. IEEE Transactions on Fuzzy Systems, 30, 5128–5142. https://doi.org/10.1109/TFUZZ.2022.3167789

[10] Qi, Z., Zhi, H., & Ding, W. (2025). Distributed conflict analysis across varying analysis levels based on fuzzy formal contexts. Information Sciences, 707, 122038. https://doi.org/10.1016/j.ins.2025.122038

[11] Wang, T., Qi, Z., Liu, T., & Zhi, H. (2026). A conflict resolution method for uncertain environment based on fuzzy concept lattice. International Journal of Approximate Reasoning, 197, 109723. https://doi.org/10.1016/j.ijar.2026.109723

[12] Tang, X., Yan, M., Li, J., & Hao, F. (2025). Information fusion based conflict analysis model for multi-source fuzzy data. International Journal of Approximate Reasoning, 185, 109472. https://doi.org/10.1016/j.ijar.2025.109472

[13] Luo, J., Hu, M., Lang, G., Yang, X., & Qin, K. (2022). Three-way conflict analysis based on alliance and conflict functions. Information Sciences, 594, 322–359. https://doi.org/10.1016/j.ins.2022.01.067

Downloads

Published

02-11-2026

Issue

Section

Articles