# Measuring and Ranking Bipolarity via Orthopairs

### Zoltán Csajbók

#### 2023

#### Abstract

Orthopairs, i.e., disjoint sets, are reasonable means to represent bipolar information. Bipolarity has different models; we use the well-known Dubois-Prade typology. Of course, bipolarity can also carry uncertainty. In this paper, we investigate mainly the bipolarity of type II. In Pawlak’s rough set theory, this bipolarity type, with its uncertainty, can be modeled naturally. The “positive” and “negative” sets form an orthopair whose two sets can be approximated by rough sets separately. Rough sets represented by nested sets can be considered an interval set structure. With the help of counting measure, interval numbers can be assigned to the nested sets. Then, relying on interval arithmetic, taking into account the uncertain nature of bipolarity, the degree of bipolarity can be measured, and the positive and negative sets ranked.

Download#### Paper Citation

#### in Harvard Style

Csajbók Z. (2023). **Measuring and Ranking Bipolarity via Orthopairs**. In *Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: FCTA*; ISBN 978-989-758-674-3, SciTePress, pages 338-347. DOI: 10.5220/0012180800003595

#### in Bibtex Style

@conference{fcta23,

author={Zoltán Csajbók},

title={Measuring and Ranking Bipolarity via Orthopairs},

booktitle={Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: FCTA},

year={2023},

pages={338-347},

publisher={SciTePress},

organization={INSTICC},

doi={10.5220/0012180800003595},

isbn={978-989-758-674-3},

}

#### in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Joint Conference on Computational Intelligence - Volume 1: FCTA

TI - Measuring and Ranking Bipolarity via Orthopairs

SN - 978-989-758-674-3

AU - Csajbók Z.

PY - 2023

SP - 338

EP - 347

DO - 10.5220/0012180800003595

PB - SciTePress