A Soft Set Approach for Handling Conflict Situation on Movie Selection

Conflict analysis plays an important role in the fields of politics, military operations, economics, business management, games, urban planning, management negotiations and etcetera. Computational intelligence model such as rough set theory has been used in managing conflict situations which have th...

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Veröffentlicht in:IEEE access 2019, Vol.7, p.116179-116194
Hauptverfasser: Haruna, Khalid, Ismail, Maizatul Akmar, Suyanto, Mohammad, Gabralla, Lubna A., Bichi, Abdullahi Baffa, Danjuma, Sani, Adamu Kakudi, Habeebah, Haruna, Muhammad Sani, Zerdoumi, Saber, Abawajy, Jemal H., Herawan, Tutut
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Sprache:eng
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Zusammenfassung:Conflict analysis plays an important role in the fields of politics, military operations, economics, business management, games, urban planning, management negotiations and etcetera. Computational intelligence model such as rough set theory has been used in managing conflict situations which have the ability to handle uncertainties. However, there is a great concern in the computational time of the rough set approach in determining strength, certainty and coverage of conflicts. Motivated by the fact that every rough set approach can be represented using soft set theory, we derived an alternative method based on the concept of co-occurrence from multi-soft sets to handle conflict situations. We first used an illustrative example of a movie selection problem to demonstrate the proposed approach and provide an extensive elaboration using a publicly available dataset. Our motivation is to provide a new measure based on support, strength, certainty and coverage of soft set on movie selection problem. Our findings have revealed that the proposed approach achieved less computational time when compared with the rough set-based approach of up to 8.05%. One potential application of the proposed approach is the domain of recommendation systems. The proposed approach can be used to easily identify users/items nearest neighbours based on support, strength, certainty and coverage, which is crucial for the success of recommendation systems.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2892778