Johannes Fürnkranz

Johannes Fürnkranz, Dragan Gamberger, Nada Lavrac: Foundations of Rule Learning. Cognitive Technologies, Springer 2012, isbn 978-3-540-75196-0, pp. 1-298

Sang-Hyeun Park, Johannes Fürnkranz: Efficient prediction algorithms for binary decomposition techniques. Data Min. Knowl. Discov. 24(1): 40-77 (2012)

Johannes Fürnkranz, Eyke Hüllermeier, Weiwei Cheng, Sang-Hyeun Park: Preference-based reinforcement learning: a formal framework and a policy iteration algorithm. Machine Learning 89(1-2): 123-156 (2012)

Johannes Fürnkranz, Sang-Hyeun Park: Error-Correcting Output Codes as a Transformation from Multi-Class to Multi-Label Prediction. Discovery Science 2012: 254-267

Wouter Duivesteijn, Eneldo Loza Mencía, Johannes Fürnkranz, Arno J. Knobbe: Multi-label LeGo - Enhancing Multi-label Classifiers with Local Patterns. IDA 2012: 114-125

Heiko Paulheim, Johannes Fürnkranz: Unsupervised generation of data mining features from linked open data. WIMS 2012: 31

Lars Wohlrab, Johannes Fürnkranz: A review and comparison of strategies for handling missing values in separate-and-conquer rule learning. J. Intell. Inf. Syst. 36(1): 73-98 (2011)

Eyke Hüllermeier, Johannes Fürnkranz: Learning from Label Preferences. ALT 2011: 38

Eyke Hüllermeier, Johannes Fürnkranz: Learning from Label Preferences. Discovery Science 2011: 2-17

Jan-Nikolas Sulzmann, Johannes Fürnkranz: Rule Stacking: An Approach for Compressing an Ensemble of Rule Sets into a Single Classifier. Discovery Science 2011: 323-334

Frederik Janssen, Johannes Fürnkranz: Heuristic Rule-Based Regression via Dynamic Reduction to Classification. IJCAI 2011: 1330-1335

Weiwei Cheng, Johannes Fürnkranz, Eyke Hüllermeier, Sang-Hyeun Park: Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning. ECML/PKDD (1) 2011: 312-327

Marco Ghiglieri, Johannes Fürnkranz: Learning to Recognize Missing E-Mail Attachments. Applied Artificial Intelligence 24(5): 443-462 (2010)

Johannes Fürnkranz, Arno J. Knobbe: Guest Editorial: Global modeling using local patterns. Data Min. Knowl. Discov. 21(1): 1-8 (2010)

Eneldo Loza Mencía, Sang-Hyeun Park, Johannes Fürnkranz: Efficient voting prediction for pairwise multilabel classification. Neurocomputing 73(7-9): 1164-1176 (2010)

Eyke Hüllermeier, Johannes Fürnkranz: On predictive accuracy and risk minimization in pairwise label ranking. J. Comput. Syst. Sci. 76(1): 49-62 (2010)

Frederik Janssen, Johannes Fürnkranz: On the quest for optimal rule learning heuristics. Machine Learning 78(3): 343-379 (2010)

Johannes Fürnkranz, Jan Frederik Sima: On exploiting hierarchical label structure with pairwise classifiers. SIGKDD Explorations 12(2): 21-25 (2010)

Sang-Hyeun Park, Lorenz Weizsäcker, Johannes Fürnkranz: Exploiting Code Redundancies in ECOC. Discovery Science 2010: 266-280

Eneldo Loza Mencía, Johannes Fürnkranz: Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain. Semantic Processing of Legal Texts 2010: 192-215

Johannes Fürnkranz: Web Mining. Data Mining and Knowledge Discovery Handbook 2010: 913-929

Nada Lavrac, Johannes Fürnkranz, Dragan Gamberger: Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms. Advances in Machine Learning I 2010: 121-146

Johannes Fürnkranz: Decision List. Encyclopedia of Machine Learning 2010: 261

Johannes Fürnkranz: Decision Lists and Decision Trees. Encyclopedia of Machine Learning 2010: 261-262

Johannes Fürnkranz: Decision Tree. Encyclopedia of Machine Learning 2010: 263-267

Johannes Fürnkranz: Machine Learning and Game Playing. Encyclopedia of Machine Learning 2010: 633-637

Johannes Fürnkranz, Eyke Hüllermeier: Preference Learning. Encyclopedia of Machine Learning 2010: 789-795

Johannes Fürnkranz: Pruning. Encyclopedia of Machine Learning 2010: 817

Johannes Fürnkranz: Rule Learning. Encyclopedia of Machine Learning 2010: 875-879

Johannes Fürnkranz, Thorsten Joachims (Eds.): Proceedings of the 27th International Conference on Machine Learning (ICML-10), June 21-24, 2010, Haifa, Israel. Omnipress 2010, isbn 978-1-60558-907-7

Jan-Nikolas Sulzmann, Johannes Fürnkranz: An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules. Discovery Science 2009: 317-331

Eneldo Loza Mencía, Sang-Hyeun Park, Johannes Fürnkranz: Efficient voting prediction for pairwise multilabel classification. ESANN 2009

Immanuel Schweizer, Kamill Panitzek, Sang-Hyeun Park, Johannes Fürnkranz: An Exploitative Monte-Carlo Poker Agent. KI 2009: 65-72

Sang-Hyeun Park, Johannes Fürnkranz: Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification. ECML/PKDD (2) 2009: 189-204

Johannes Fürnkranz, Eyke Hüllermeier, Stijn Vanderlooy: Binary Decomposition Methods for Multipartite Ranking. ECML/PKDD (1) 2009: 359-374

Frederik Janssen, Johannes Fürnkranz: A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. SDM 2009: 329-340

Eyke Hüllermeier, Johannes Fürnkranz, Weiwei Cheng, Klaus Brinker: Label ranking by learning pairwise preferences. Artif. Intell. 172(16-17): 1897-1916 (2008)

Sacha Droste, Johannes Fürnkranz: Learning the Piece Values for Three Chess Variants. ICGA Journal 31(4): 209-233 (2008)

Johannes Fürnkranz, Eyke Hüllermeier, Eneldo Loza Mencía, Klaus Brinker: Multilabel classification via calibrated label ranking. Machine Learning 73(2): 133-153 (2008)

Frederik Janssen, Johannes Fürnkranz: An Empirical Investigation of the Trade-Off between Consistency and Coverage in Rule Learning Heuristics. Discovery Science 2008: 40-51

Eneldo Loza Mencía, Johannes Fürnkranz: Pairwise learning of multilabel classifications with perceptrons. IJCNN 2008: 2899-2906

Frederik Janssen, Johannes Fürnkranz: A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. LWA 2008: 42-49

Jan-Nikolas Sulzmann, Johannes Fürnkranz: A Comparison of Techniques for Selecting and Combining Class Association Rules. LWA 2008: 87-93

Eneldo Loza Mencía, Johannes Fürnkranz: Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain. ECML/PKDD (2) 2008: 50-65

Dragan Gamberger, Nada Lavrac, Johannes Fürnkranz: Handling Unknown and Imprecise Attribute Values in Propositional Rule Learning: A Feature-Based Approach. PRICAI 2008: 636-645

Jan-Nikolas Sulzmann, Johannes Fürnkranz, Eyke Hüllermeier: On Pairwise Naive Bayes Classifiers. ECML 2007: 371-381

Eyke Hüllermeier, Johannes Fürnkranz: On Minimizing the Position Error in Label Ranking. ECML 2007: 583-590

Sang-Hyeun Park, Johannes Fürnkranz: Efficient Pairwise Classification. ECML 2007: 658-665

Frederik Janssen, Johannes Fürnkranz: On Meta-Learning Rule Learning Heuristics. ICDM 2007: 529-534

Eneldo Loza Mencía, Johannes Fürnkranz: An Evaluation of Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain. LWA 2007: 126-132

Frederik Janssen, Johannes Fürnkranz: Meta-Learning Rule Learning Heuristics. LWA 2007: 167-174

Michael H. Bowling, Johannes Fürnkranz, Thore Graepel, Ron Musick: Machine learning and games. Machine Learning 63(3): 211-215 (2006)

Klaus Brinker, Johannes Fürnkranz, Eyke Hüllermeier: A Unified Model for Multilabel Classification and Ranking. ECAI 2006: 489-493

Frederik Janssen, Johannes Fürnkranz: On Trading Off Consistency and Coverage in Inductive Rule Learning. LWA 2006: 306-313

Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou (Eds.): Machine Learning: ECML 2006, 17th European Conference on Machine Learning, Berlin, Germany, September 18-22, 2006, Proceedings. Lecture Notes in Computer Science 4212, Springer 2006, isbn 3-540-45375-X

Johannes Fürnkranz, Tobias Scheffer, Myra Spiliopoulou (Eds.): Knowledge Discovery in Databases: PKDD 2006, 10th European Conference on Principles and Practice of Knowledge Discovery in Databases, Berlin, Germany, September 18-22, 2006, Proceedings. Lecture Notes in Computer Science 4213, Springer 2006, isbn 3-540-45374-1

Johannes Fürnkranz, Eyke Hüllermeier: Preference Learning. KI 19(1): 60- (2005)

Johannes Fürnkranz, Peter A. Flach: ROC 'n' Rule Learning-Towards a Better Understanding of Covering Algorithms. Machine Learning 58(1): 39-77 (2005)

Johannes Fürnkranz: Web Mining. The Data Mining and Knowledge Discovery Handbook 2005: 899-920

Hervé Utard, Johannes Fürnkranz: Link-Local Features for Hypertext Classification. EWMF/KDO 2005: 51-64

Eyke Hüllermeier, Johannes Fürnkranz: Learning Label Preferences: Ranking Error Versus Position Error. IDA 2005: 180-191

Eyke Hüllermeier, Johannes Fürnkranz, Jürgen Beringer: On Position Error and Label Ranking through Iterated Choice. LWA 2005: 158-163

Mathias Bauer, Boris Brandherm, Johannes Fürnkranz, Gunter Grieser, Andreas Hotho, Andreas Jedlitschka, Alexander Kröner (Eds.): Lernen, Wissensentdeckung und Adaptivität (LWA) 2005, GI Workshops, Saarbrücken, October 10th-12th, 2005. DFKI 2005

Johannes Fürnkranz: From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms. Local Pattern Detection 2004: 20-38

Johannes Fürnkranz, Peter A. Flach: An Analysis of Stopping and Filtering Criteria for Rule Learning. ECML 2004: 123-133

Johannes Fürnkranz: Modeling Rule Precision. LWA 2004: 147-154

Johannes Fürnkranz: Round robin ensembles. Intell. Data Anal. 7(5): 385-403 (2003)

Johannes Fürnkranz, Eyke Hüllermeier: Pairwise Preference Learning and Ranking. ECML 2003: 145-156

Johannes Fürnkranz, Peter A. Flach: An Analysis of Rule Evaluation Metrics. ICML 2003: 202-209

Petr Savický, Johannes Fürnkranz: Combining Pairwise Classifiers with Stacking. IDA 2003: 219-229

Johannes Fürnkranz, Christian Holzbaur, Robert Temel: User Profiling for the MELVIL Knowledge Retrieval System. Applied Artificial Intelligence 16(4): 243-281 (2002)

Johannes Fürnkranz: Hyperlink ensembles: a case study in hypertext classification. Information Fusion 3(4): 299-312 (2002)

Johannes Fürnkranz: Round Robin Classification. Journal of Machine Learning Research 2: 721-747 (2002)

Johannes Fürnkranz: A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning. ALT 2002: 263-277

Johannes Fürnkranz: Pairwise Classification as an Ensemble Technique. ECML 2002: 97-110

Johannes Fürnkranz: Round Robin Rule Learning. ICML 2001: 146-153

Alexander K. Seewald, Johannes Fürnkranz: An Evaluation of Grading Classifiers. IDA 2001: 115-124

Hendrik Blockeel, Johannes Fürnkranz, Alexia Prskawetz, Francesco C. Billari: Detecting Temporal Change in Event Sequences: An Application to Demographic Data. PKDD 2001: 29-41

Klaus Kovar, Johannes Fürnkranz, Johann Petrak, Bernhard Pfahringer, Robert Trappl, Gerhard Widmer: Searching for Patterns in Political Event Sequences: Experiments with the Keds Database. Cybernetics and Systems 31(6): 649-668 (2000)

Johannes Fürnkranz, Bernhard Pfahringer, Hermann Kaindl, Stefan Kramer: Learning to Use Operational Advice. ECAI 2000: 291-295

Johannes Fürnkranz: Separate-and-Conquer Rule Learning. Artif. Intell. Rev. 13(1): 3-54 (1999)

Johannes Fürnkranz: Exploiting Structural Information for Text Classification on the WWW. IDA 1999: 487-498

Johannes Fürnkranz, Bernhard Pfahringer: Guest Editorial: First-Order Knowledge Discovery in Databases. Applied Artificial Intelligence 12(5): 345-361 (1998)

Johannes Fürnkranz: Integrative Windowing. J. Artif. Intell. Res. (JAIR) 8: 129-164 (1998)

Johannes Fürnkranz: Integrative Windowing. CoRR cs.AI/9805101 (1998)

Johannes Fürnkranz, Johann Petrak, Robert Trappl: Knowledge Discovery in International Conflict Databases. Applied Artificial Intelligence 11(2): 91-118 (1997)

Johannes Fürnkranz: Pruning Algorithms for Rule Learning. Machine Learning 27(2): 139-172 (1997)

Franz-Günter Winkler, Johannes Fürnkranz: On Effort in AI Research: A Description Along Two Dimensions. Deep Blue Versus Kasparov: The Significance for Artificial Intelligence 1997: 56-62

Johannes Fürnkranz: More Efficient Windowing. AAAI/IAAI 1997: 509-514

Johannes Fürnkranz: Noise-Tolerant Windowing. IJCAI (2) 1997: 852-859

Robert Trappl, Johannes Fürnkranz, Johann Petrak: Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases. ECAI 1996: 453-457

Johannes Fürnkranz: A Tight Integration of Pruning and Learning (Extended Abstract). ECML 1995: 291-294

Johannes Fürnkranz: Top-Down Pruning in Relational Learning. ECAI 1994: 453-457

Johannes Fürnkranz: FOSSIL: A Robust Relational Learner. ECML 1994: 122-137

Johannes Fürnkranz, Gerhard Widmer: Incremental Reduced Error Pruning. ICML 1994: 70-77

Johannes Fürnkranz: A Comparison of Pruning Methods for Relational Concept Learning. KDD Workshop 1994: 371-382