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

Fober, T., Eyke Hüllermeier, and M. Mernberger. “Evolutionary Construction of Multiple Graph Alignments for Mining Structured Biomolecular Data .” In In Proceedings Workshop LWA-2008, Lernen-Wissensentdeckung-Adaptivität, Würzburg, Germany, 27–33, 2008.

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

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

Hüllermeier, Eyke, J. Fürnkranz, W. Cheng, and K. Brinker. “Label Ranking by Learning Pairwise Preferences.” Artificial Intelligence 172 (2008): 1897–1917.

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

Fürnkranz, J., Eyke Hüllermeier, E. Mencia, and K. Brinker. “Multilabel Classification via Calibrated Label Ranking.” Machine Learning 73, no. 2 (2008): 133–53.

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

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

Hüllermeier, Eyke. “Granular Computing in Machine Learning and Data Mining.” In Handbook on Granular Computing, edited by W. Pedrycz, A. Skowron, and V. Kreinovich, 889–906. John Wiley and Sons, 2008.

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

Hüllermeier, Eyke, and J. Fürnkranz. “Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants.” In Preferences and Similarities, edited by G. Della Riccia, D. Dubois, R. Kruse, and H.J. Lenz, 283–304. Preferences and Similarities. Springer, 2008.

Hüllermeier, Eyke, I. Vladimirskiy, B. Prados Suarez, and E. Stauch. “Supporting Case-Based Retrieval by Similarity Skylines: Basic Concepts and Extensions.” In In Proceedings ECCBR-2008 9th European Conference on Case-Based  Reasoning, Trier, Germany, edited by K.D. Althoff, R. Bergmann, M. Minor, and A. Hanft, 240–54, 2008.

Cheng, W., and Eyke Hüllermeier. “Learning Similarity Functions from Qualitative Feedback.” In In Proceedings ECCBR-2008 9th European Conference on Case-Based  Reasoning, Trier, Germany, edited by K.D. Althoff, R. Bergmann, M. Minor, and A. Hanft, 120–34. Springer, 2008.

Cheng, W., Eyke Hüllermeier, B. Seeger, and I. Vladimirskiy. “Interactive Ranking of Skylines Using Machine Learning Techniques.” In In Proceedings Workshop LWA-2007, Lernen-Wissensentdeckung-Adaptivität, Halle/Saale, Germany, 141–48, 2007.

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

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

Hüllermeier, Eyke, and J. Fürnkranz. “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.

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

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

Brinker, K., and Eyke Hüllermeier. “Case-Based Multilabel Ranking.” In In Proceedings IJCAI-07, 20th International Joint Conference on Artificial Intelligence, Hyerabad, India, January 2007, 701–7, 2007.

Hüllermeier, Eyke, and K. Brinker. “Fuzzy-Relational Classificatonf: 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, 1:353–60, 2007.

Beringer, J., and Eyke Hüllermeier. “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.

Hüllermeier, Eyke, N. Weskamp, G. Klebe, and D. Kuhn. “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.

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

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

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

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

Weskamp, N., Eyke Hüllermeier, D. Kuhn, and G. Klebe. “Multiple Graph Aligment for the Structural Analysis of Protein Active Sites.” IEEE/ACM Transactions of Computational Biology and Bioinformatics 4, no. 2 (2007): 310–20.

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

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

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

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

Hüllermeier, Eyke. Case-Based Approximate Reasoning. Vol. 44. Series B: Mathematical and Statistical Methods. Springer, 2007.

Sulzmann, J.N., J. Fürnkranz, and Eyke Hüllermeier. “On Pairwise Naive Bayes Classifiers.” In 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 In Proceedings 16th Workshop Computational Intelligence, Dortmund Germany, edited by R. Mikut and M. Reischl, 140–49, 2006.

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

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

Bade, K., Eyke Hüllermeier, and A. Nürnberger. “Hierarchical Classification by Expected Utility Maximization.” In In Proceedings ICDM-2006, IEEE International Conference on Data Mining, 43–52. IEEE Computer Society Press, 2006.

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

Brinker, K., J. Fuernkranz, and Eyke Hüllermeier. “A Unified Model for Multilabel Classification and Ranking.” In In Proceedings ECAI-2006, 17th European Conference on Artificial Inteligence, Riva Del Garda, Italy, edited by G. Brewka, S. Coradeschi, A. Perini, and P. Traverso, 489–93, 2006.

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

Dubois, D., Eyke Hüllermeier, and H. Prade. “A Systematic Approach to the Assessment of Fuzzy Association Rules.” Data Mining and Knowledge Discovery 13, no. 2 (2006): 167–92.

Dubois, D., Eyke Hüllermeier, and H. Prade. “Fuzzy Methods in Case-Based Recommendation and Decision Support.” Journal of Intelligent Information Systems 27 (2006): 95–115.

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

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

Karimi, I., Eyke Hüllermeier, and K. Meskouris. “A Fuzzy-Probablistic Earthquake Risk Assessment System.” Soft Computing 11, no. 3 (2006): 229–38.

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

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

Hüllermeier, Eyke, and Cho-k NN. “A Method for Combining Interacting Pieces of Evidence in Case-Based Learning.” In In Proceedings IJCAI-05, 19th International Joint Conference on Artificial Intelligence, Edingburgh, Scotland, edited by L. Kaelbling and A. Saffiotti, 3–8, 2005.

Hüllermeier, Eyke, and J. Fürnkranz. “Learning Label Preferences: Ranking Error versus Position Error.” In In Proceedings IDA-2005, 6th International Symposium on Intelligent Data Analysis, Madrid, edited by A. Famili, J. Kok, J. Pena, A. Siebes, and A. Feelders, 3646:180–91. LNCS. Springer, 2005.

Hüllermeier, Eyke, and J. Beringer. “Learning from Ambiguously Labeled Examples.” In In Proceedings IDA-2005, 6th International Symposium on Intelligent Data Analysis, Madrid, edited by A. Famili, J. Kok, J. Pena, A. Siebes, and A. Feelders, 3646:168–79. LNAI. Springer, 2005.

Dubois, D., and Eyke Hüllermeier. “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., and Eyke Hüllermeier. “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, 1147–53, 2005.

Lughofer, E., Eyke Hüllermeier, and E. Klement. “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., and Eyke Hüllermeier. “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, Eyke. “Fuzzy Sets in Machine Learning and Data Mining: Status and Prospects.” Fuzzy Sets and Systems 156, no. 3 (2005): 387–406.

Hüllermeier, Eyke. “Experience-Based Decision Making: A Satisficing Decision Tree Approach.” IEEE Transactions on Systems, Man and Cybernetics-Part A: Systems and Humans 35, no. 5 (2005): 641–53.

Balasubramaniyan, R., Eyke Hüllermeier, N. Weskamp, and J. Kämper. “Clustering of Gene Expression Data Using a Local Shape-Based Similarity Measure.” Bioinformatics 21, no. 7 (2005): 1069–77.

Dubois, D., Eyke Hüllermeier, and H. Prade. “A Systematic Approach to the Assessment of Fuzzy Association Rules.” In In Proceedings of the Workshop on Alternative Techniques for Data Mining and Knowledge Discovery, IEEE International Conference on Data Mining, Brighton, UK, edited by JC. Cubero, D. Sanchez, Z. Ras, and T. Sudkamp, 2004.

Weskamp, N., Eyke Hüllermeier, D. Kuhn, and G. Klebe. “Graph Alignments: A New Concept to Detect Conserved Regions in Protein Active Sites.” In In Proceedings of GCB-2004 of the German Conference on Bioinformatics, Bielefeld, Germany, edited by R. Giegerich and J. Stoye, 131–40. Lecture Notes in Informatics, Bielefeld, Germany. Springer, 2004.

Hüllermeier, Eyke. “Instance-Based Prediction with Guaranteed Confidence.” In In Proceedings ECAI-2004, 16th European Conference on Artificial Inteligence, Valencia, Spain, edited by R. Lopez de Mantaras and L. Saitta, 97–101. IOS Press, 2004.

Hüllermeier, Eyke, and J. Fürnkranz. “Comparison of Ranking Procedures in Pairwise Preference Learning.” In In Proceedings IPMU-2004 10th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Perugia, Italy, 2004.

Hüllermeier, Eyke, and J. Fürnkranz. “Ranking by Pairwise Comparison: A Note on Risk Minimization.” In In Proceedings FUZZ-IEEE-04, IEEE International Conference on Fuzzy Systems, Budapest, Hungary, 2004.

Karimi, I., Eyke Hüllermeier, and K. Meskouris. “An Earthquake Risk Assessment Method Based on Fuzzy Probability.” In In Proceedings 6th International FLINS Conference on Applied  Computational Intelligence, Duinse Polders, Blankenberg,Belgien, 2004.

Hüllermeier, Eyke, and J. Beringer. “Learning Decision Rules from Positive and Negative Preferences.” In In Proceedings IPMU-2004 10th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems, Perugia, Italy, 2004.

Hüllermeier, Eyke, I. Renners, and A. Grauel. “An Evolutionary Approach to Constraints-Regularized Learning.” Mathware and Soft Computing 11, no. 2–3 (2004): 109–24.

Weskamp, N., D. Kuhn, Eyke Hüllermeier, and G. Klebe. “Efficient Similarity Search in Protein Structure Databases: Improving Clique-Detection through Clique-Hashing.” Bioinformatics 20, no. 10 (2004): 1522–26.

Hüllermeier, Eyke. “Flexible Constraints for Regularization in Learning from Data.” International Journal of Intelligent Systems 19, no. 6 (2004): 525–41.

Weskamp, N., D. Kuhn, Eyke Hüllermeier, and G. Klebe. “Efficient Similarity Search in Protein Structure Databases: Improving Clique-Detection through Geometric Hashing.” In In Proceedings GCB-2003 German Conference on Bioinformatics, Munich, Germany, 2003.

Hüllermeier, Eyke. “Instance-Based Learning of Credible Label Sets.” In In Proceedings KI-2003, 26th German Conference on Artificial Intelligence, Hamburg, Germany, edited by A. Günter, R. Kruse, and B. Neumann. 2821 in Lecture Notes in Artificial Intelligence, Hamburg, Germany. Springer, 2003.

Hüllermeier, Eyke. “Regularized Learning with Flexible Constraints.” In In Proceddings IDA-03, 5th International Symposium on Intelligent Data Anaysis, edited by M.R. Berthold, H.J. Lenz, E. Bradley, R. Kruse, and C. Borgelt, Vol. 2810.  Lecture Notes in Computer Science, Berlin. Springer, 2003.

Fürnkranz, J., and Eyke Hüllermeier. “Pairwise Preference Learning and Ranking.” In In Proceedings ECML-2003, 13 Th European Conference on Machine Learning, Cavtat-Dubrovnik, Croatia. Springer, 2003.

Hüllermeier, Eyke. “Instance-Based Collaborative Filtering with Fuzzy Labels.” In In Proceedings EUSFLAT-2003 3th International Conference on the European Society for Fuzzy Logic and Technology, Zittlau, Germany, 468–73, 2003.

Dubois, D., Eyke Hüllermeier, and H. Prade. “A Note on Quality Measures for Fuzzy Association Rules.” In In Proceedings IFSA-03 10th International Fuzzy Systems Association World Congress, Istanbul, Turkey, edited by T. Bilgic, B. De Beats, and O. Kaynak, 2715:648–77. LNAI. Springer, 2003.

Hüllermeier, Eyke. “Inducing Fuzzy Concepts through Extended Version Space Learning.” In In Proceedings IFSA-03 10th International Fuzzy Systems Association World Congress, Istanbul, Turkey, edited by T. Bilgic, B. De Beats, and O. Kaynak, 2715:648–77. LNAI. Springer, 2003.

Hüllermeier, Eyke. “Possibilistic Instance-Based Learning.” Artificial Intelligence 148, no. 1–2 (2003): 335–83.

De Calmès, M., D. Dubois, Eyke Hüllermeier, H. Prade, and F. Sèdes. “Flexibility and Case-Based Evaluation in Querying: An Illustration in an Experimental Setting.” International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 11, no. 1 (2003): 43–66.

Dubois, D., Eyke Hüllermeier, and H. Prade. “On the Representation of Fuzzy Rules in Terms of Crisp Rules.” Information Sciences 151 (2003): 301–26.

Hüllermeier, Eyke. “Sequential Decision Making in Heuristic Search.” In Planning Based on Decision Theory (CISM Courses and Lectures No.472), edited by G. Della Riccia, D. Dubois, R. Kruse, and H.J. Lenz. Springer, 2003.

Dubois, D., Eyke Hüllermeier, and H. Prade. “Possibilistic Case-Based Decisions.” In Connectionist Approaches in Economics and Management  Sciences, edited by C. Lesage and M. Cottrell, Vol. 6. Advances in Computational Management Sciences. Kluwer, 2003.

Hüllermeier, Eyke, and J. Beringer. “Mining Implication-Based Fuzzy Association Rules in Databases.” In Intelligent Systems for Information Processing: From Representation to Applications, edited by B. Bouchon-Meunier, L. Foulloy, and R.R.. Yager. Elsevier, 2003.

Hüllermeier, Eyke. “On the Representation and Combination of Evidence in Instance-Based Learning.” In In Proceedings ECAI-2002, 15th European Conference on Artificial Intelligence, Lyon, France, 360–64. IOS Press, 2002.

De Calmès, M., D. Dubois, Eyke Hüllermeier, H. Prade, and F. Sèdes. “A Fuzzy Set Approach to Flexible Case-Based Querying: Methodology and Experimentation.” In In Proceedings KR-02, 8th International Conference on Principles of Knowledge Representation and Reasoning, France, edited by D. Fensel, F. Giunchiglia, D. Mc Guinness, and M.A. Williams, 449–58. Morgan Kaufmann, 2002.

Hüllermeier, Eyke. “Association Rules for Expressing Gradual Dependencies.” In In Proceedings PKDD-02  6th European Conference on Principles and Practise of Knowledge Discovery in Databases, Helsinki, Finland, 200–211. Springer, 2002.

Hüllermeier, Eyke. “Possibilistic Induction in Decision Tree Learning.” In In Proceedings ECML-02, 13th European Conference on Machine Learning, Helsinki Finland, 173–84. Springer, 2002.

Hüllermeier, Eyke. “Mining Implication-Based Fuzzy Association Rules in Databases.” In In Proceedings IPMU-2002 9th International Conference on Information Processing and Management  of Uncertainty in Knowledge-Based Systems,Annecy, France, 101–8, 2002.

Hüllermeier, Eyke. “Exploiting Similarity and Experience in Decision Making.” In In Proceedings FUZZ-IEEE-02, IEEE International Conference on Fuzzy Systems, Honolulu, Hawaii, 729–34, 2002.

De Calmès, M., D. Dubois, Eyke Hüllermeier, H. Prade, and F. Sèdes. “Case-Based Quering and Prediction: A Fuzzy Set Approach.” In In Proceedings FUZZ-IEEE-02, IEEE International Conference on Fuzzy Systems, Honolulu, Hawaii, 735–40, 2002.

Hüllermeier, Eyke, D. Dubois, and H. Prade. “Model Adaption in Possibilistic Instance-Based Reasoning.” IEEE Transactions on Fuzzy Systems 10, no. 3 (2002): 333–39.

Dubois, D., Eyke Hüllermeier, and H. Prade. “Fuzzy Set-Based Methods in Instance-Based Reasoning.” IEEE Transactions on Fuzzy Systems 10, no. 3 (2002): 322–32.

Hüllermeier, Eyke, D. Dubois, and H. Prade. “Knowledge-Based Extrapolation of Cases: A Possibilistic Approach.” In Technologies for Constructing Intelligent Systems, edited by B. Bouchon-Meunier, J. Gutierrez-Rios, L. Magdalena, and R.R. Yager, 377–90. Springer, 2002.

Hüllermeier, Eyke. “Experience-Based Decision Making and Learning from Examples.” In In Proceedings SOR-01 Symposium on Operations Research, Duisburg, Germany. Springer, 2001.

Hüllermeier, Eyke. “Possibilistic Instance-Based Learning.” In In Proceedings FGML-2001 German Workshop on Machine Learning, Dortmund, Germany, 108–15, 2001.

Hüllermeier, Eyke. “Implication-Based Fuzzy Association Rules.” In In Proceedings FGML-2001 German Workshop on Machine Learning, Dortmund, Germany, 93–99, 2001.

Hüllermeier, Eyke, D. Dubois, and H. Prade. “Instance-Based Prediction in the Framework of Possibility Theory.” In In Proceedings of Workshop on Soft Computing in Case-Based Reasoning, Vancouver, Canada, 2001.

Hüllermeier, Eyke. “Implication-Based Fuzzy Association Rules.” In In Proceedings PKDD-01  5th European Conference on Principles and Practise of Knowledge Discovery in Databases, Freiburg, Germany, edited by De. Raedt and A. Siebes, 2168:241–52. LNAI. Springer, 2001.

Hüllermeier, Eyke. “Fuzzy Association Rules: Semantic Issues and Quality Measures.” In In Proceedings of the International Conference on Computational Intelligence 7th Fuzzy Days, Dortmund, Germany, edited by B. Reusch, 2206:380–91. LNCS. Springer, 2001.

Dubois, D., Eyke Hüllermeier, and H. Prade. “Toward the Representation of Implication-Based Fuzzy Rules in Terms of Crisp Rules.” In In Proceedings IFSA/NAFIPS-2001  Joint 9th World Congress of the International Fuzzy Systems Association and 20th Internatinonal Conference of the North American Fuzzy Information Processing Society, Vancouver, Canada, 1592–97, 2001.