Abstract
With the growing popularity of movies as a source of entertainment and relaxation in modern society, movie recommendation systems have become increasingly important for helping viewers navigate a vast selection of movie products. However, existing methods may not accurately capture the preferences and opinions of viewers. To address this gap, we propose a novel approach that utilizes the Pythagorean hesitant fuzzy distance measure in combination with the VIKOR method to deal with the extracted review information and evaluate the similarity between different movies in a given genre. We then transform this information into Pythagorean hesitant fuzzy attribute evaluation terms using the Probabilistic Linguistic Term Set (PLTS) and apply conflict degree theory to calculate similarity scores. The algorithm proposed in this paper employs the VIKOR method to select recommended movie products that match the preferences of users and satisfy their needs. Comparative analysis demonstrates its reliability and stability. In addition, according to the comparative data, its performance is better than the comparable method in the selection of alternative schemes, which highlights its contribution in the field of movie recommendation systems.
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Funding
This work was supported by the 2022 Henan Philosophy and Social Science Planning Project (Grant No. 2022BXW001), Key R&D and Promotion Special Project (Soft Science Research) of Science and Technology Department of Henan Province in 2023 (Grant No. 232400411049), Ministry of Education Humanities and social sciences research planning fund project (Grant No. 23YJA860004), Major project of basic research on Philosophy and Social Sciences in Colleges and Universities of Henan Province (Grant No. 2024-JCZD-27) and Science and technology research project of Henan Provincial Department of science and technology.
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Cui, C., Wei, M., Che, L. et al. Movie Recommendation Algorithms Based on an Improved Pythagorean Hesitant Fuzzy Distance Measure and VIKOR Method. Int. J. Fuzzy Syst. 26, 513–526 (2024). https://doi.org/10.1007/s40815-023-01611-0
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DOI: https://doi.org/10.1007/s40815-023-01611-0