Abstract
The article presents a system of election recommendation in which both candidate’s and voter’s preferences can be described in an imprecise way. The model of the system is based on IF-set theory which can express hesitation or lack of knowledge. Similarity measures of IF-sets and linguistic quantifiers are used in the decision-making process.
Research supported by Ministry of Science and Higher Education Grant N N519 384936.
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Dyczkowski, K., Stachowiak, A. (2012). A Recommender System with Uncertainty on the Example of Political Elections. In: Greco, S., Bouchon-Meunier, B., Coletti, G., Fedrizzi, M., Matarazzo, B., Yager, R.R. (eds) Advances in Computational Intelligence. IPMU 2012. Communications in Computer and Information Science, vol 298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31715-6_47
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DOI: https://doi.org/10.1007/978-3-642-31715-6_47
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