Hühn, J., and Eyke Hüllermeier. “FURIA: An Algorithm for Unordered Fuzzy Rule Induction.” Data Mining and Knowledge Discovery , vol. 19, 2009, pp. 293–319.
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Hüllermeier, Eyke, and S. Vanderlooy. “Why Fuzzy Decision Trees Are Good Rankers.” IEEE Transactions on Fuzzy Systems, vol. 17, no. 6, 2009, pp. 1233–44.
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Yi, Y., et al. “Fuzzy Operator Trees for Modeling Rating Functions.” International Journal of Computational Intelligence and Applications, vol. 8, no. 4, 2009, pp. 413–28.
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Fober, T., et al. “Evolutionary Construction of Multiple Graph Alignments for the Structural Analysis of Biomolecules.” Bioinformatics, vol. 25, no. 16, 2009, pp. 2110–17.
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Hühn, J., and Eyke Hüllermeier. “F: A Fuzzy Rule Learner for Inducing Reliable Classifiers.” IEEE Transactions on Fuzzy Systems, vol. 17, no. 1, 2009, pp. 138–49.
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Hüllermeier, Eyke, et al. “Supporting Case-Based Retrieval by Similarity Skylines: Basic Concepts and Extensions.” Künstliche Intelligenz, vol. 1, no. 09, 2009, pp. 24–29.
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Hüllermeier, Eyke. “On the Usefulness of Fuzzy Sets in Data Mining.” Views on Fuzzy Sets and Systems from Different Perspectives: Philosophy and Logic, Criticisms and Applications, edited by R. Seising, Springer, 2009, pp. 457–70.
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Cheng, W., et al. “Decision Tree and Instance-Based Learning for Label Ranking.” In Proceedings ICML-2009, 26th International Conference on Machine Learning, Montreal, Canada, 2009, pp. 161–68.
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Fürnkranz, J., et al. “Binary Decomposition Methods for Multipartite Ranking.” In Proceedings ECML/PKDD-2009, European Conference on Machine Learning and Principles and Knowledge Discovery in Databases, Bled Sloveniaery in Databases, Bled, Slovenia, 2009.
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Cheng, W., and Eyke Hüllermeier. “A New Instance-Based Label Ranking Approach Using the Mallows Model. In Advances in Neural Networks.” In Proceedings 6th International Symposium on Neural Networks, Wuhan, China, no. LNCS 5551, Springer, 2009, pp. 707–16.
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