Brinker K, Fuernkranz J, Hüllermeier E. A unified model for multilabel classification and ranking. In: Brewka G, Coradeschi S, Perini A, Traverso P, eds. In Proceedings ECAI-2006, 17th European Conference on Artificial Inteligence, Riva Del Garda, Italy. ; 2006:489-493.

Hüllermeier E. Integrating instance-based learning and logistic regression. In: In Proceedings IPMU-2006 11th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Paris, France. ; 2006.

Hüllermeier E. The Choquet integral as an aggregation operator in case-based learning. In: Reusch B, ed. In Proceeding of the International Conference on Computational Intelligence, 9th Fuzzy Days, Dortmund. Springer; 2006:615-628.

Dubois D, Hüllermeier E, Prade H. A systematic approach to the assessment of fuzzy association rules. Data Mining and Knowledge Discovery. 2006;13(2):167-192.

Dubois D, Hüllermeier E, Prade H. Fuzzy methods in case-based recommendation and decision support. Journal of Intelligent Information Systems. 2006;27:95-115.

Hüllermeier E, Beringer J. Learning from ambiguously labeled examples. Intelligent Data Analysis. 2006;10(5):419-440.

Beringer J, Hüllermeier E. Online clustering of parallel data streams. Data and Knowledge Engineering. 2006;58(2):180-204.

Karimi I, Hüllermeier E, Meskouris K. A fuzzy-probablistic earthquake risk assessment system. Soft Computing. 2006;11(3):229-238.

Brinker K, Hüllermeier E. Calibrated label-ranking. In: Agarwal S, Cortes C, Herbrich R, eds. In Proceedings of the NIPS-2005 Workshop on Learning to Rank, Whistler, BC, Canada. http://web.mit.edu/shivani/www/Ranking-NIPS-05/.; 2005:1-6.

Hüllermeier E, Fürnkranz J, Beringer J. On position error and label ranking through iterated choice. In: In Proceedings LWA/FGML-2005, German Workshop on Machine Learning, Saarbrücken, Germany . ; 2005:158-163.

Hüllermeier E, NN C. A method for combining interacting pieces of evidence in case-based learning. In: Kaelbling L, Saffiotti A, eds. In Proceedings IJCAI-05, 19th International Joint Conference on Artificial Intelligence, Edingburgh, Scotland. ; 2005:3-8.

Hüllermeier E, Fürnkranz J. Learning label preferences: Ranking error versus position error. In: Famili A, Kok J, Pena J, Siebes A, Feelders A, eds. In Proceedings IDA-2005, 6th International Symposium on Intelligent Data Analysis, Madrid. Vol 3646. LNCS. Springer; 2005:180-191.

Hüllermeier E, Beringer J. Learning from ambiguously labeled examples. In: Famili A, Kok J, Pena J, Siebes A, Feelders A, eds. In Proceedings IDA-2005, 6th International Symposium on Intelligent Data Analysis, Madrid. Vol 3646. LNAI. Springer; 2005:168-179.

Dubois D, Hüllermeier E. A notion of comarative probabilistic entroy based on the possibilistic specificity ordering. In: In Proceedings ECSQARU-2005, 8th European Conference of Symbolic and Quantitative Approaches to Reasoning with Uncertainty, Barcelona, Spain. ; 2005.

Karimi I, Hüllermeier E. A fuzzy-probablistic risk assessment system for natural disasters. In: In Proceedings IFSA-2005, 11th  World Congress of the International Fuzzy System Association, Beijing, China. ; 2005:1147-1153.

Lughofer E, Hüllermeier E, Klement E. Improving the interpretability of data-driven evolving fuzzy systems. In: In Proceedings EUSFLAT-2005 4th International Conference on the European Society for Fuzzy Logic and Technology, Barcelona, Spain. ; 2005.

Yi Y, Hüllermeier E. Learning complexity-boundet rule-based classifiers by combining association analysis and genetic algorithms. In: In Proceedings EUSFLAT-2005 4th International Conference on the European Society for Fuzzy Logic and Technology,  Barcelona, Spain. ; 2005.

Hüllermeier E. Fuzzy sets in machine learning and data mining: Status and prospects. Fuzzy Sets and Systems. 2005;156(3):387-406.

Hüllermeier E. Experience-based decision making: A satisficing decision tree approach. IEEE Transactions on Systems, Man and Cybernetics-Part A: Systems and Humans. 2005;35(5):641-653.

Balasubramaniyan R, Hüllermeier E, Weskamp N, Kämper J. Clustering of gene expression data using a local shape-based similarity measure. Bioinformatics. 2005;21(7):1069-1077.