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448 Publications


2009 | Journal Article | LibreCat-ID: 16159
Hüllermeier, E., & Vanderlooy, S. (2009). Why fuzzy decision trees are good rankers. IEEE Transactions on Fuzzy Systems, 17(6), 1233–1244.
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2009 | Journal Article | LibreCat-ID: 16161
Yi, Y., Fober, T., & Hüllermeier, E. (2009). Fuzzy operator trees for modeling rating functions. International Journal of Computational Intelligence and Applications, 8(4), 413–428.
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2009 | Journal Article | LibreCat-ID: 16162
Fober, T., Mernberger, M., Klebe, G., & Hüllermeier, E. (2009). Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules. Bioinformatics, 25(16), 2110–2117.
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2009 | Journal Article | LibreCat-ID: 16163
Hühn, J., & Hüllermeier, E. (2009). FR3: A fuzzy rule learner for inducing reliable classifiers. IEEE Transactions on Fuzzy Systems, 17(1), 138–149.
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2009 | Journal Article | LibreCat-ID: 16165
Hüllermeier, E., Vladimirskiy, I., Prados Suarez, B., & Stauch, E. (2009). Supporting case-based retrieval by similarity skylines: Basic concepts and extensions. Künstliche Intelligenz, 1(09), 24–29.
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2009 | Book Chapter | LibreCat-ID: 10188
Hüllermeier, E. (2009). On the usefulness of fuzzy sets in data mining. In R. Seising (Ed.), Views on Fuzzy Sets and Systems from Different Perspectives: Philosophy and Logic, Criticisms and Applications (pp. 457–470). Springer.
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2009 | Conference Paper | LibreCat-ID: 13595
Cheng, W., Hühn, J., & Hüllermeier, E. (2009). Decision tree and instance-based learning for label ranking. In in Proceedings ICML-2009, 26th International Conference on Machine Learning, Montreal, Canada (pp. 161–168).
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2009 | Conference Paper | LibreCat-ID: 13596
Fürnkranz, J., Hüllermeier, E., & Vanderlooy, S. (2009). Binary decomposition methods for multipartite ranking. In In Proceedings ECML/PKDD-2009, European Conference on Machine Learning and Principles and Knowledge Discovery in Databases, Bled Sloveniaery in Databases, Bled, Slovenia.
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2009 | Conference Paper | LibreCat-ID: 13598
Cheng, W., & Hüllermeier, E. (2009). A new instance-based label ranking approach using the Mallows model. In Advances in Neural Networks. In in Proceedings 6th International Symposium on Neural Networks, Wuhan, China (pp. 707–716). Springer.
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2008 | Conference Paper | LibreCat-ID: 15779
Hüllermeier, E., & Vanderlooy, S. (2008). Weighted voting as approximate MAP prediction in pairwise classification. In In Proceedings Workshop LWA-2008, Lernen-Wissensentdeckung-Adaptivität, Würzburg, Germany (pp. 34–41).
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2008 | Conference Paper | LibreCat-ID: 15780
Fober, T., Hüllermeier, E., & Mernberger, M. (2008). Evolutionary construction of multiple graph alignments for mining structured biomolecular data . In In Proceedings Workshop LWA-2008, Lernen-Wissensentdeckung-Adaptivität, Würzburg, Germany (pp. 27–33).
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2008 | Conference Paper | LibreCat-ID: 15781
Fober, T., Hüllermeier, E., & Mernberger, M. (2008). Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules. In A. Beyer & M. Schroeder (Eds.), iIn Proceedings GCB-2008, Germany Conference on Bioinformatics, Dresden 2008 (pp. 44–53).
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2008 | Journal Article | LibreCat-ID: 16164
Hühn, J., & Hüllermeier, E. (2008). Is an ordinal class structure useful in classifier learning? International Journal of Data Mining, Modeling and Management , 1(1), 45–67.
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2008 | Journal Article | LibreCat-ID: 16166
Hüllermeier, E., Fürnkranz, J., Cheng, W., & Brinker, K. (2008). Label ranking by learning pairwise preferences. Artificial Intelligence, 172, 1897–1917.
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2008 | Journal Article | LibreCat-ID: 16167
Vanderlooy, S., & Hüllermeier, E. (2008). A critical analysis of variants of the AUC. Machine Learning, 72, 247–272.
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2008 | Journal Article | LibreCat-ID: 16168
Fürnkranz, J., Hüllermeier, E., Mencia, E., & Brinker, K. (2008). Multilabel classification via calibrated label ranking. Machine Learning, 73(2), 133–153.
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2008 | Journal Article | LibreCat-ID: 16169
Hüllermeier, E., & Brinker, K. (2008). Learning valued preference structures for solving classification problems. Fuzzy Sets and Systems, 159(18), 2337–2352.
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2008 | Journal Article | LibreCat-ID: 16184
Beringer, J., & Hüllermeier, E. (2008). Case-based learning in a bipolar possibilistic framework. International Journal of Intelligent Systems, 23(10), 1119–1134.
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2008 | Book Chapter | LibreCat-ID: 16225
Hüllermeier, E. (2008). Granular computing in machine learning and data mining. In W. Pedrycz, A. Skowron, & V. Kreinovich (Eds.), Handbook on Granular Computing (pp. 889–906). John Wiley and Sons.
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2008 | Book Chapter | LibreCat-ID: 10154
Hüllermeier, E. (2008). Fuzzy methods in data mining. In Encyclopedia of Data Warehousing and Mining - Second Edition (pp. 907–912). Idea Group, Inc.,Hershey, USA.
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