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448 Publications


2009 | Conference Paper | LibreCat-ID: 15774
Senge R, Hüllermeier E. Learning pattern tree classifiers using a co-evolutionary algorithm. In: Hoffmann F, Hüllermeier E, eds. In Proceedings 19th Workshop Computational Intelligence, Dortmund Germany. KIT Scientific Publishing; 2009:22-33.
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2009 | Conference Paper | LibreCat-ID: 15775
Fober T, Mernberger M, Moritz R, Hüllermeier E. Graph-kernels for the comparative analysis of protein active sites. In: Grosse I, Neumann S, Posch S, Schreiber F, Stadler P., eds. In Proceedings GCB-2009 German Conference on Bioinformatics Halle (Saale), Germany. ; 2009:21-31.
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2009 | Conference Paper | LibreCat-ID: 15776
Senge R, Hüllermeier E. Learning pattern tree classifiers using a co-evolutionary algorithm. In: In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Darmstadt, Germany. ; 2009:105-110.
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2009 | Conference Paper | LibreCat-ID: 15778
Fober T, Mernberger M, Melnikov V, Moritz R, Hüllermeier E. Extension and empirical comparison of graph-kernels for the analysis of protein active sites. In: In Proceedings Workshop LWA-2009, Lernen-Wissensentdeckung-Adaptivität, Darmstadt, Germany. ; 2009:30-36.
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2009 | Conference Paper | LibreCat-ID: 15120
Fober T, Klebe G, Hüllermeier E. Efficient construction of multiple geometrical alignments for the comparison of protein binding sites. In: In Proceedings ISDA-2009, 9th International Conference on Intelligent Systems Design and Applications, Pisa, Italy. ; 2009:1251-1256.
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2009 | Conference Paper | LibreCat-ID: 15194
Boukhris I, Elouedi Z, Fober T, Mernberger M, Hüllermeier E. Similarity analysis of protein binding sites: A generalization of the maximum common subgraph measure based on quasi-clique detection. In: In Proceedings IDA-2009, 9th International Symposium on Intelligent Data Analysis, Pisa / Italy. ; 2009:1245-1250.
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2009 | Conference Paper | LibreCat-ID: 15195
Fober T, Hüllermeier E. Fuzzy modeling of labeled point cloud superposition  for the comparison of protein binding sites. In: In Proceedings IFSA / EUSFLAT-2009 World Congress of  the Fuzzy Systems Association, Lissabon, Portugal. ; 2009:1299-1304.
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2009 | Conference Paper | LibreCat-ID: 15196
Hüllermeier E, Rifqi M. A fuzzy variant of the Rand index for comparing clustering structures. In: In Proceedings IFSA / EUSFLAT-2009 World Congress of  the Fuzzy Systems Association, Lissabon, Portugal. ; 2009:1294-1298.
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2009 | Journal Article | LibreCat-ID: 16154
Weskamp N, Hüllermeier E, Klebe G. Merging chemical and biological space: Structural mapping of enzyme binding pocket space. Proteins. 2009;76(2):317-330.
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2009 | Journal Article | LibreCat-ID: 16158
Hühn J, Hüllermeier E. FURIA: An Algorithm for unordered fuzzy rule induction. Data Mining and Knowledge Discovery . 2009;19:293-319.
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2009 | Journal Article | LibreCat-ID: 16159
Hüllermeier E, Vanderlooy S. Why fuzzy decision trees are good rankers. IEEE Transactions on Fuzzy Systems. 2009;17(6):1233-1244.
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2009 | Journal Article | LibreCat-ID: 16161
Yi Y, Fober T, Hüllermeier E. Fuzzy operator trees for modeling rating functions. International Journal of Computational Intelligence and Applications. 2009;8(4):413-428.
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2009 | Journal Article | LibreCat-ID: 16162
Fober T, Mernberger M, Klebe G, Hüllermeier E. Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules. Bioinformatics. 2009;25(16):2110-2117.
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2009 | Journal Article | LibreCat-ID: 16163
Hühn J, Hüllermeier E. FR3: A fuzzy rule learner for inducing reliable classifiers. IEEE Transactions on Fuzzy Systems. 2009;17(1):138-149.
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2009 | Journal Article | LibreCat-ID: 16165
Hüllermeier E, Vladimirskiy I, Prados Suarez B, Stauch E. Supporting case-based retrieval by similarity skylines: Basic concepts and extensions. Künstliche Intelligenz. 2009;1(09):24-29.
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2009 | Book Chapter | LibreCat-ID: 10188
Hüllermeier E. On the usefulness of fuzzy sets in data mining. In: Seising R, ed. Views on Fuzzy Sets and Systems from Different Perspectives: Philosophy and Logic, Criticisms and Applications. Springer; 2009:457-470.
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2009 | Conference Paper | LibreCat-ID: 13595
Cheng W, Hühn J, Hüllermeier E. Decision tree and instance-based learning for label ranking. In: In Proceedings ICML-2009, 26th International Conference on Machine Learning, Montreal, Canada. ; 2009:161-168.
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2009 | Conference Paper | LibreCat-ID: 13596
Fürnkranz J, Hüllermeier E, Vanderlooy S. 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. ; 2009.
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2009 | Conference Paper | LibreCat-ID: 13598
Cheng W, Hüllermeier E. 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. Springer; 2009:707-716.
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2008 | Conference Paper | LibreCat-ID: 15779
Hüllermeier E, Vanderlooy S. Weighted voting as approximate MAP prediction in pairwise classification. In: In Proceedings Workshop LWA-2008, Lernen-Wissensentdeckung-Adaptivität, Würzburg, Germany. ; 2008:34-41.
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2008 | Conference Paper | LibreCat-ID: 15780
Fober T, Hüllermeier E, Mernberger M. Evolutionary construction of multiple graph alignments for mining structured biomolecular data . In: In Proceedings Workshop LWA-2008, Lernen-Wissensentdeckung-Adaptivität, Würzburg, Germany. ; 2008:27-33.
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2008 | Conference Paper | LibreCat-ID: 15781
Fober T, Hüllermeier E, Mernberger M. Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules. In: Beyer A, Schroeder M, eds. IIn Proceedings GCB-2008, Germany Conference on Bioinformatics, Dresden 2008. ; 2008:44-53.
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2008 | Journal Article | LibreCat-ID: 16164
Hühn J, Hüllermeier E. Is an ordinal class structure useful in classifier learning? International Journal of Data Mining, Modeling and Management . 2008;1(1):45-67.
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2008 | Journal Article | LibreCat-ID: 16166
Hüllermeier E, Fürnkranz J, Cheng W, Brinker K. Label ranking by learning pairwise preferences. Artificial Intelligence. 2008;172:1897-1917.
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2008 | Journal Article | LibreCat-ID: 16167
Vanderlooy S, Hüllermeier E. A critical analysis of variants of the AUC. Machine Learning. 2008;72:247-272.
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2008 | Journal Article | LibreCat-ID: 16168
Fürnkranz J, Hüllermeier E, Mencia E, Brinker K. Multilabel classification via calibrated label ranking. Machine Learning. 2008;73(2):133-153.
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2008 | Journal Article | LibreCat-ID: 16169
Hüllermeier E, Brinker K. Learning valued preference structures for solving classification problems. Fuzzy Sets and Systems. 2008;159(18):2337-2352.
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2008 | Journal Article | LibreCat-ID: 16184
Beringer J, Hüllermeier E. Case-based learning in a bipolar possibilistic framework. International Journal of Intelligent Systems. 2008;23(10):1119-1134.
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2008 | Book Chapter | LibreCat-ID: 16225
Hüllermeier E. Granular computing in machine learning and data mining. In: Pedrycz W, Skowron A, Kreinovich V, eds. Handbook on Granular Computing. John Wiley and Sons; 2008:889-906.
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2008 | Book Chapter | LibreCat-ID: 10154
Hüllermeier E. Fuzzy methods in data mining. In: Encyclopedia of Data Warehousing and Mining - Second Edition. Idea Group, Inc.,Hershey, USA; 2008:907-912.
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2008 | Book Chapter | LibreCat-ID: 10185
Hüllermeier E, Fürnkranz J. Learning preference models from data: On the problem of label ranking and its variants. In: Della Riccia G, Dubois D, Kruse R, Lenz HJ, eds. Preferences and Similarities. Preferences and Similarities. Springer; 2008:283-304.
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2008 | Conference Paper | LibreCat-ID: 13599
Hüllermeier E, Vladimirskiy I, Prados Suarez B, Stauch E. Supporting case-based retrieval by similarity skylines: Basic concepts and extensions. In: Althoff KD, Bergmann R, Minor M, Hanft A, eds. In Proceedings ECCBR-2008 9th European Conference on Case-Based  Reasoning, Trier, Germany. ; 2008:240-254.
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2008 | Conference Paper | LibreCat-ID: 13600
Cheng W, Hüllermeier E. Learning similarity functions from qualitative feedback. In: Althoff KD, Bergmann R, Minor M, Hanft A, eds. In Proceedings ECCBR-2008 9th European Conference on Case-Based  Reasoning, Trier, Germany. Springer; 2008:120-134.
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2007 | Conference Paper | LibreCat-ID: 15782
Cheng W, Hüllermeier E, Seeger B, Vladimirskiy I. Interactive ranking of skylines using machine learning techniques. In: In Proceedings Workshop LWA-2007, Lernen-Wissensentdeckung-Adaptivität, Halle/Saale, Germany. ; 2007:141-148.
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2007 | Conference Paper | LibreCat-ID: 15783
Fober T, Hüllermeier E, Mernberger M. Evolutionary construction of multiple graph alignments for the structural analysis of biomolecules. In: Mikut R, Reischl M, eds. In Proceedings 17th Workshop Computational Intelligence, Dortmund Germany. ; 2007:1-14.
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2007 | Conference Paper | LibreCat-ID: 15784
Vladimirskiy I, Hüllermeier E, Stauch E. Similarity search over uncertain archaeological data using a modified skyline operator. In: Wilson DC, Khemani D, eds. In Workshop Proceedings from ICCBR-2007 7th International Conference on Case-Based Reasoning, Belfast, Northern Ireland. ; 2007:31-40.
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2007 | Conference Paper | LibreCat-ID: 14832
Hüllermeier E, Fürnkranz J. On minimizing the position error in label ranking. In: In Proceedings ECML-2007, 17th European Conference on Machine Learning, Warsawa, Poland, September 2007. Springer; 2007.
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2007 | Conference Paper | LibreCat-ID: 14833
Brinker K, Hüllermeier E. Label ranking in case-based reasoning. In: Richter M, Weber R, eds. In Proceedings ICCBR-2007, 7th International Conference on Case-Based Reasoning, Belfast, Northern Ireland. Vol 4626. LNAI. Springer; 2007:77-91.
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2007 | Conference Paper | LibreCat-ID: 14834
Beringer J, Hüllermeier E. Efficient instance-based learning on data streams. In: Perner P, ed. In Proceedings ICDM-2007, International Conference on Industrial Data Mining, Leipzig. Springer; 2007:34-48.
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2007 | Conference Paper | LibreCat-ID: 14835
Brinker K, Hüllermeier E. Case-based multilabel ranking. In: In Proceedings IJCAI-07, 20th International Joint Conference on Artificial Intelligence, Hyerabad, India, January 2007. ; 2007:701-707.
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2007 | Conference Paper | LibreCat-ID: 15197
Hüllermeier E, Brinker K. Fuzzy-relational classificaton : Combining pairwise decomposition techniques with fuzzy preference modeling. In: In Proceedings EUSFLAT-2007 5th International Conference on the European Society for Fuzzy Logic and Technology, Ostrava, Czech Republic. Vol 1. ; 2007:353-360.
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2007 | Conference Paper | LibreCat-ID: 15198
Beringer J, Hüllermeier E. Adaptive optimization of the number of clusters in fuzzy clustering, London 2007. In: In Proceedings FUZZ-IEEE-07, IEEE International Conference on Fuzzy Systems. ; 2007.
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2007 | Conference Paper | LibreCat-ID: 15199
Hüllermeier E, Weskamp N, Klebe G, Kuhn D. Graph alignment: Fuzzy pattern mining for the structural analysis of protein active sites. In: In Proceedings FUZZ-IEEE-07, IEEE International Conference on Fuzzy Systems, London. ; 2007.
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2007 | Journal Article | LibreCat-ID: 16170
Hüllermeier E, Yi Y. In defense of fuzzy association analysis. IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics. 2007;37(4):1039-1043.
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2007 | Journal Article | LibreCat-ID: 16171
Hüllermeier E. Credible case-based inference using similarity profiles. IEEE Transactions on Knowledge and Data Engineering. 2007;19(5):847-858.
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2007 | Journal Article | LibreCat-ID: 16172
Beringer J, Hüllermeier E. Efficient instance-based learning on data streams. Intelligent Data Analysis. 2007;11(6):627-650.
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2007 | Journal Article | LibreCat-ID: 16175
Dubois D, Hüllermeier E. Comparing probability measures using possibility theory: A notion of relative peakedness. International Journal of Approximate Reasoning. 2007;45(2):364-385.
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2007 | Journal Article | LibreCat-ID: 16179
Weskamp N, Hüllermeier E, Kuhn D, Klebe G. Multiple graph aligment for the structural analysis of protein active sites. IEEE/ACM Transactions of Computational Biology and Bioinformatics. 2007;4(2):310-320.
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2007 | Journal Article | LibreCat-ID: 16194
Karimi I, Hüllermeier E. Risk assessment for natural hazards: A new approach based on fuzzy probability. Fuzzy Sets and Systems. 2007;158(9):987-999.
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2007 | Book Chapter | LibreCat-ID: 16224
Hüllermeier E. Why fuzzy set theory is useful in data mining. In: Masseglia F, Poncelet P, Teisseire M, eds. Successes and New Directions in Data Mining. Information Science Reference, Hershey, New York; 2007:1-16.
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