Hüllermeier, Eyke, and S. Vanderlooy. “Weighted Voting as Approximate MAP Prediction in Pairwise Classification.” In Proceedings Workshop LWA-2008, Lernen-Wissensentdeckung-Adaptivität, Würzburg, Germany, 2008, pp. 34–41.

Fober, T., et al. “Evolutionary Construction of Multiple Graph Alignments for Mining Structured Biomolecular Data .” In Proceedings Workshop LWA-2008, Lernen-Wissensentdeckung-Adaptivität, Würzburg, Germany, 2008, pp. 27–33.

Fober, T., et al. “Evolutionary Construction of Multiple Graph Alignments for the Structural Analysis of Biomolecules.” IIn Proceedings GCB-2008, Germany Conference on Bioinformatics, Dresden 2008, edited by A. Beyer and M. Schroeder, 2008, pp. 44–53.

Hühn, J., and Eyke Hüllermeier. “Is an Ordinal Class Structure Useful in Classifier Learning?” International Journal of Data Mining, Modeling and Management , vol. 1, no. 1, 2008, pp. 45–67.

Hüllermeier, Eyke, et al. “Label Ranking by Learning Pairwise Preferences.” Artificial Intelligence, vol. 172, 2008, pp. 1897–917.

Vanderlooy, S., and Eyke Hüllermeier. “A Critical Analysis of Variants of the AUC.” Machine Learning, vol. 72, 2008, pp. 247–72.

Fürnkranz, J., et al. “Multilabel Classification via Calibrated Label Ranking.” Machine Learning, vol. 73, no. 2, 2008, pp. 133–53.

Hüllermeier, Eyke, and K. Brinker. “Learning Valued Preference Structures for Solving Classification Problems.” Fuzzy Sets and Systems, vol. 159, no. 18, 2008, pp. 2337–52.

Beringer, J., and Eyke Hüllermeier. “Case-Based Learning in a Bipolar Possibilistic Framework.” International Journal of Intelligent Systems, vol. 23, no. 10, 2008, pp. 1119–34.

Hüllermeier, Eyke. “Granular Computing in Machine Learning and Data Mining.” Handbook on Granular Computing, edited by W. Pedrycz et al., John Wiley and Sons, 2008, pp. 889–906.

Hüllermeier, Eyke. “Fuzzy Methods in Data Mining.” Encyclopedia of Data Warehousing and Mining - Second Edition, Idea Group, Inc.,Hershey, USA, 2008, pp. 907–12.

Hüllermeier, Eyke, and J. Fürnkranz. “Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants.” Preferences and Similarities, edited by G. Della Riccia et al., Springer, 2008, pp. 283–304.

Hüllermeier, Eyke, et al. “Supporting Case-Based Retrieval by Similarity Skylines: Basic Concepts and Extensions.” In Proceedings ECCBR-2008 9th European Conference on Case-Based  Reasoning, Trier, Germany, edited by K.D. Althoff et al., no. LNAI 5239, 2008, pp. 240–54.

Cheng, W., and Eyke Hüllermeier. “Learning Similarity Functions from Qualitative Feedback.” In Proceedings ECCBR-2008 9th European Conference on Case-Based  Reasoning, Trier, Germany, edited by K.D. Althoff et al., no. LNAI 5239, Springer, 2008, pp. 120–34.

Cheng, W., et al. “Interactive Ranking of Skylines Using Machine Learning Techniques.” In Proceedings Workshop LWA-2007, Lernen-Wissensentdeckung-Adaptivität, Halle/Saale, Germany, 2007, pp. 141–48.

Fober, T., et al. “Evolutionary Construction of Multiple Graph Alignments for the Structural Analysis of Biomolecules.” In Proceedings 17th Workshop Computational Intelligence, Dortmund Germany, edited by R. Mikut and M. Reischl, 2007, pp. 1–14.

Vladimirskiy, I., et al. “Similarity Search over Uncertain Archaeological Data Using a Modified Skyline Operator.” In Workshop Proceedings from ICCBR-2007 7th International Conference on Case-Based Reasoning, Belfast, Northern Ireland, edited by D.C. Wilson and D. Khemani, 2007, pp. 31–40.

Hüllermeier, Eyke, and J. Fürnkranz. “On Minimizing the Position Error in Label Ranking.” In Proceedings ECML-2007, 17th European Conference on Machine Learning, Warsawa, Poland, September 2007, Springer, 2007.

Brinker, K., and Eyke Hüllermeier. “Label Ranking in Case-Based Reasoning.” In Proceedings ICCBR-2007, 7th International Conference on Case-Based Reasoning, Belfast, Northern Ireland, edited by M. Richter and R. Weber, vol. 4626, Springer, 2007, pp. 77–91.

Beringer, J., and Eyke Hüllermeier. “Efficient Instance-Based Learning on Data Streams.” In Proceedings ICDM-2007, International Conference on Industrial Data Mining, Leipzig, edited by P. Perner, Springer, 2007, pp. 34–48.

Brinker, K., and Eyke Hüllermeier. “Case-Based Multilabel Ranking.” In Proceedings IJCAI-07, 20th International Joint Conference on Artificial Intelligence, Hyerabad, India, January 2007, 2007, pp. 701–07.

Hüllermeier, Eyke, and K. Brinker. “Fuzzy-Relational Classificatonf: Combining Pairwise Decomposition Techniques with Fuzzy Preference Modeling.” In Proceedings EUSFLAT-2007 5th International Conference on the European Society for Fuzzy Logic and Technology, Ostrava, Czech Republic, vol. 1, 2007, pp. 353–60.

Beringer, J., and Eyke Hüllermeier. “Adaptive Optimization of the Number of Clusters in Fuzzy Clustering, London 2007.” In Proceedings FUZZ-IEEE-07, IEEE International Conference on Fuzzy Systems, 2007.

Hüllermeier, Eyke, et al. “Graph Alignment: Fuzzy Pattern Mining for the Structural Analysis of Protein Active Sites.” In Proceedings FUZZ-IEEE-07, IEEE International Conference on Fuzzy Systems, London, 2007.

Hüllermeier, Eyke, and Y. Yi. “In Defense of Fuzzy Association Analysis.” IEEE Transactions on Systems, Man and Cybernetics-Part B: Cybernetics, vol. 37, no. 4, 2007, pp. 1039–43.

Hüllermeier, Eyke. “Credible Case-Based Inference Using Similarity Profiles.” IEEE Transactions on Knowledge and Data Engineering, vol. 19, no. 5, 2007, pp. 847–58.

Beringer, J., and Eyke Hüllermeier. “Efficient Instance-Based Learning on Data Streams.” Intelligent Data Analysis, vol. 11, no. 6, 2007, pp. 627–50.

Dubois, D., and Eyke Hüllermeier. “Comparing Probability Measures Using Possibility Theory: A Notion of Relative Peakedness.” International Journal of Approximate Reasoning, vol. 45, no. 2, 2007, pp. 364–85.

Weskamp, N., et al. “Multiple Graph Aligment for the Structural Analysis of Protein Active Sites.” IEEE/ACM Transactions of Computational Biology and Bioinformatics, vol. 4, no. 2, 2007, pp. 310–20.

Karimi, I., and Eyke Hüllermeier. “Risk Assessment for Natural Hazards: A New Approach Based on Fuzzy Probability.” Fuzzy Sets and Systems, vol. 158, no. 9, 2007, pp. 987–99.

Hüllermeier, Eyke. “Why Fuzzy Set Theory Is Useful in Data Mining.” Successes and New Directions in Data Mining, edited by F. Masseglia et al., Information Science Reference, Hershey, New York, 2007, pp. 1–16.

Beringer, J., and Eyke Hüllermeier. “Fuzzy Clustering of Parallel Data Streams.” Advances in Fuzzy Clustering and Its Applications , edited by J. Valente de Oliveira and W. Pedrycz, John Wiley and Sons, 2007, pp. 333–52.

Hüllermeier, Eyke. “Fuzzy Methods for Data Mining and Machine Learning: State of the Art and Prospects.” Fuzzy Sets and Their Extensions: Representation, Aggregation and Models, Springer, 2007, pp. 355–74.

Hüllermeier, Eyke. Case-Based Approximate Reasoning. Vol. 44, Springer, 2007.

Sulzmann, J. N., et al. “On Pairwise Naive Bayes Classifiers.” In Proceedings ECML-2007, 17th European Conference on Machine Learning, Warsawa, Poland, Springer, 2007.

Beringer, J., and Eyke Hüllermeier. “Adaptive Optimization of the Number of Clusters in Fuzzy Clustering, Dortmund, Germany 2006.” In Proceedings 16th Workshop Computational Intelligence, Dortmund Germany, edited by R. Mikut and M. Reischl, 2006, pp. 140–49.

Hüllermeier, Eyke, and K. Brinker. “Classification via Fuzzy Preference Learning.” In Proceedings 16th Workshop Computational Intelligence, Dortmund Germany, edited by R. Mikut and M. Reischl, 2006, pp. 190–99.

Hüllermeier, Eyke. “Credible Case-Based Inference Using Similarity Profiles.” In Proceedings of ECCBR-2006 Workshops, 8th European Conference on Case-Based Reasoning, Ölüdeniz/Fethiye Turkey, edited by M. Minor, 2006, pp. 230–42.

Bade, K., et al. “Hierarchical Classification by Expected Utility Maximization.” In Proceedings ICDM-2006, IEEE International Conference on Data Mining, IEEE Computer Society Press, 2006, pp. 43–52.

Brinker, K., and Eyke Hüllermeier. “Case-Based Label Ranking.” In Proceedings ECML-2006, 17th European Conference on Machine Learning, Berlin September 2006, Springer, 2006, pp. 566–73.

Brinker, K., et al. “A Unified Model for Multilabel Classification and Ranking.” In Proceedings ECAI-2006, 17th European Conference on Artificial Inteligence, Riva Del Garda, Italy, edited by G. Brewka et al., 2006, pp. 489–93.

Hüllermeier, Eyke. “Integrating Instance-Based Learning and Logistic Regression.” In Proceedings IPMU-2006 11th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Paris, France, 2006.

Hüllermeier, Eyke. “The Choquet Integral as an Aggregation Operator in Case-Based Learning.” In Proceeding of the International Conference on Computational Intelligence, 9th Fuzzy Days, Dortmund, edited by B. Reusch, Springer, 2006, pp. 615–28.

Dubois, D., et al. “A Systematic Approach to the Assessment of Fuzzy Association Rules.” Data Mining and Knowledge Discovery, vol. 13, no. 2, 2006, pp. 167–92.

Dubois, D., et al. “Fuzzy Methods in Case-Based Recommendation and Decision Support.” Journal of Intelligent Information Systems, vol. 27, 2006, pp. 95–115.

Hüllermeier, Eyke, and J. Beringer. “Learning from Ambiguously Labeled Examples.” Intelligent Data Analysis, vol. 10, no. 5, 2006, pp. 419–40.

Beringer, J., and Eyke Hüllermeier. “Online Clustering of Parallel Data Streams.” Data and Knowledge Engineering, vol. 58, no. 2, 2006, pp. 180–204.

Karimi, I., et al. “A Fuzzy-Probablistic Earthquake Risk Assessment System.” Soft Computing, vol. 11, no. 3, 2006, pp. 229–38.

Brinker, K., and Eyke Hüllermeier. “Calibrated Label-Ranking.” In Proceedings of the NIPS-2005 Workshop on Learning to Rank, Whistler, BC, Canada, edited by S. Agarwal et al., http://web.mit.edu/shivani/www/Ranking-NIPS-05/., 2005, pp. 1–6.

Hüllermeier, Eyke, et al. “On Position Error and Label Ranking through Iterated Choice.” In Proceedings LWA/FGML-2005, German Workshop on Machine Learning, Saarbrücken, Germany , 2005, pp. 158–63.