Johannes Fürnkranz
First name(s): Johannes
Last name(s): Fürnkranz

Publications of Johannes Fürnkranz
2021
Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz and Hüllermeier Eyke, Gradient-Based Label Binning in Multi-Label Classification, in: Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), Springer, 2021
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Moritz Kulessa, Eneldo Loza Mencía and Johannes Fürnkranz, Revisiting Non-Specific Syndromic Surveillance, in: Advances in Intelligent Data Analysis {XIX} - 19th International Symposium on Intelligent Data Analysis, {IDA} 2021, Porto, Portugal, April 26-28, 2021, Proceedings, pages 128-140, Springer International Publishing, 2021
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Moritz Kulessa, Bennet Wittelsbach, Eneldo Loza Mencía and Johannes Fürnkranz, Sum-Product Networks for Early Outbreak Detection of Emerging Diseases, in: Artificial Intelligence in Medicine, pages 61--71, Springer International Publishing, 2021
2020
Tomás Kliegr, Štépán Bahník and Johannes Fürnkranz, Advances in Machine Learning for the Behavioral Sciences (2020), in: American Behavioral Scientist, 64:2(145--175)
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Eyke Hüllermeier, Johannes Fürnkranz and Eneldo Loza Mencía, Conformal Rule-Based Multi-label Classification, in: KI 2020: Advances in Artificial Intelligence, Springer, Cham, 2020
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Moritz Kulessa, Eneldo Loza Mencía and Johannes Fürnkranz, Improving the Fusion of Outbreak Detection Methods with Supervised Learning, in: Computational Intelligence Methods for Bioinformatics and Biostatistics - 16th International Meeting, {CIBB} 2019, Bergamo, Italy, September 4-6, 2019, Revised Selected Papers, Bergamo, Italy, pages 55--66, Springer, 2020
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Michael Rapp, Eneldo Loza Mencía, Johannes Fürnkranz, Vu-Linh Nguyen and Eyke Hüllermeier, Learning Gradient Boosted Multi-label Classification Rules, in: Machine Learning and Knowledge Discovery in Databases (ECML-PKDD), pages 124--140, Springer, 2020
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Vu-Linh Nguyen, Eyke Hüllermeier, Michael Rapp, Eneldo Loza Mencía and Johannes Fürnkranz, On Aggregation in Ensembles of Multilabel Classifiers, in: Discovery Science, pages 533--547, Springer International Publishing, 2020
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2019
Lukas Fleckenstein, Sebastian Kauschke and Johannes Fürnkranz, Beta Distribution Drift Detection for Adaptive Classifiers, in: Proceedings of the 2019 European Symposium on Artificial Neural Networks -- ESANN'19, 2019
Hien Quoc Dang and Johannes Fürnkranz, Driver Information Embedding with Siamese LSTM networks, in: 2019 IEEE Intelligent Vehicles Symposium (IV), Paris, France, IEEE, 2019
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Moritz Kulessa, Eneldo Loza Mencía and Johannes Fürnkranz, Improving Outbreak Detection with Stacking of Statistical Surveillance Methods, in: Workshop Proceedings of epiDAMIK: Epidemiology meets Data Mining and Knowledge discovery (held in conjunction with ACM SIGKDD 2019), Anchorage, USA, 2019
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Aïssatou Diallo, Markus Zopf and Johannes Fürnkranz, Learning Analogy-Preserving Sentence Embeddings for Answer Selection, in: Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), pages 910--919, Association for Computational Linguistics, 2019
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Jinseok Nam, Young{-}Bum Kim, Eneldo Loza Mencía, Sunghyun Park, Ruhi Sarikaya and Johannes Fürnkranz, Learning Context-dependent Label Permutations for Multi-label Classification, in: Proceedings of the 36th International Conference on Machine Learning (ICML-19), pages 4733--4742, {PMLR}, 2019
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Michael Rapp, Eneldo Loza Mencía and Johannes Fürnkranz, On the Trade-off Between Consistency and Coverage in Multi-label Rule Learning Heuristics, Knowledge Engineering Group, Technische Universität Darmstadt, number 1908.03032, ArXiv e-prints, 2019
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Sebastian Kauschke, David Hermann Lehmann and Johannes Fürnkranz, Patching Deep Neural Networks for Nonstationary Environments, in: Proceedings of the 2019 International Joint Conference on Neural Networks -- IJCNN'19, 2019
Michael Rapp, Eneldo Loza Mencía and Johannes Fürnkranz, Simplifying Random Forests: On the Trade-off between Interpretability and Accuracy, Knowledge Engineering Group, Technische Universität Darmstadt, number 1911.04393, ArXiv e-prints, 2019
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2018
Sebastian Kauschke and Johannes Fürnkranz, Batchwise Patching of Classifiers, in: Proceedings of the 32nd AAAI Conference on Artificial Intelligence (AAAI-18), pages 3374--3381, 2018
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Michael Rapp, Eneldo Loza Mencía and Johannes Fürnkranz, Exploiting Anti-monotonicity of Multi-label Evaluation Measures for Inducing Multi-label Rules, in: PAKDD 2018: Advances in Knowledge Discovery and Data Mining, pages 29--42, Springer International Publishing, 2018
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Hien Quoc Dang and Johannes Fürnkranz, Exploiting Maneuver Dependency for Personalization of a Driver Model, in: Proceedings of the Conference ``Lernen, Wissen, Daten, Analysen'' ({LWDA}-18), pages 93--97, CEUR-WS.org, 2018
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Hien Quoc Dang and Johannes Fürnkranz, Exploiting Maneuver Dependency for Personalization of Driver Assistance Systems, in: 12. Uni-DAS e.V. Workshop Fahrerassistenz und automatisiertes Fahren. Uni-DAS, pages 106--115, 2018
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Iryna Gurevych, Christian M. Meyer, Carsten Binnig, Johannes Fürnkranz, Kristian Kersting, Stefan Roth and Edwin Simpson, Interactive Data Analytics for the Humanities, in: Proceedings of the 18th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing-17), pages 527--549, Springer-Verlag, 2018
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Eneldo Loza Mencía, Johannes Fürnkranz, Eyke Hüllermeier and Michael Rapp, Learning Interpretable Rules for Multi-label Classification, in: Explainable and Interpretable Models in Computer Vision and Machine Learning, pages 81--113, Springer-Verlag, 2018
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Sebastian Kauschke, Max Mühlhäuser and Johannes Fürnkranz, Leveraging Reproduction-Error Representations for Multi-Instance Classification, in: Proceedings of the 21st International Conference on Discovery Science - DS'18, Limassol, Cyprus, pages 83-95, Springer Nature Switzerland AG, 2018
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Tobias Joppen, Christian Wirth and Johannes Fürnkranz, Preference-Based Monte Carlo Tree Search, in: Proceedings of the 41st German Conference on Artficial Intelligence (KI-18), pages 327--340, Springer, 2018
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Johannes Fürnkranz and Tomás Kliegr, The Need for Interpretability Biases, in: Proceedings of the 17th International Symposium on Intelligent Data Analysis (IDA-18), 's-Hertogenbosch, the Netherlands, pages 15--27, Springer-Verlag, 2018
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Sebastian Kauschke, Max Mühlhäuser and Johannes Fürnkranz, Towards Semi-Supervised Classification of Event Streams via Denoising Autoencoders, in: Proceedings of the 17th IEEE International Conference on Machine Learning and Applications (ICMLA-18), pages 131--136, IEEE, 2018
Hien Quoc Dang and Johannes Fürnkranz, Using Past Maneuver Executions for Personalization of a Driver Model, in: Proceedings of the 21th IEEE International Conference on Intelligent Transportation Systems (ITSC-18), Maui, Hawaii, pages 742--748, IEEE, 2018
Markus Zopf, Teresa Botschen, Tobias Falke, Benjamin Heinzerling, Ana Marasovic, Todor Mihaylov, Avinesh P.V.S., Eneldo Loza Mencía, Johannes Fürnkranz and Anette Frank, What’s important in a text? An extensive evaluation of linguistic annotations for summarization, in: Proceedings of the 5th International Conference on Social Networks Analysis, Management and Security (SNAMS-18), Valencia, Spain, pages 272--277, 2018
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Markus Zopf, Eneldo Loza Mencía and Johannes Fürnkranz, Which Scores to Predict in Sentence Regression for Text Summarization?, in: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT 2018), pages 1782--1791, 2018
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2017
Andrei Tolstikov, Frederik Janssen and Johannes Fürnkranz, Evaluation of Different Heuristics for Accommodating Asymmetric Loss Functions in Regression, in: Proceedings of the 20th International Conference on Discovery Science (DS-17), Kyoto, Japan, Springer-Verlag, 2017
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Jinseok Nam, Eneldo Loza Mencía, Hyunwoo J. Kim and Johannes Fürnkranz, Maximizing Subset Accuracy with Recurrent Neural Networks in Multi-label Classification, in: Advances in Neural Information Processing Systems 30 (NIPS-17), pages 5419--5429, 2017
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Mohammed Arif Khan, Asif Ekbal, Eneldo Loza Mencía and Johannes Fürnkranz, Multi-Objective Optimisation-based Feature Selection for Multi-Label Classification, in: Proceedings of the 22nd International Conference on Natural Language and Information Systems (NLDB-17), pages 38--41, Springer-Verlag, 2017
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Camila González, Eneldo Loza Mencía and Johannes Fürnkranz, Re-training Deep Neural Networks to Facilitate Boolean Concept Extraction, in: Proceedings of the 20th International Conference on Discovery Science (DS-17), pages 127--143, Springer-Verlag, 2017
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Hien Quoc Dang, Johannes Fürnkranz, Maximilian Hoepfl and Alexander Biedermann, Time-to-Lane-Change Prediction with Deep Learning, in: Proceedings of the 20th IEEE International Conference on Intelligent Transportation Systems (ITSC-17), IEEE, 2017
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2016
Jinseok Nam, Eneldo Loza Mencía and Johannes Fürnkranz, All-in Text: Learning Document, Label, and Word Representations Jointly, in: Proceedings of the 30th AAAI Conference on Artificial Intelligence, Phoenix, Arizona, pages 1948--1954, AAAI Press, 2016
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Markus Zopf, Eneldo Loza Mencía and Johannes Fürnkranz, Beyond Centrality and Structural Features: Learning Information Importance for Text Summarization, in: Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, Berlin, Germany, pages 84-94, Association for Computational Linguistics, 2016
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Tobias Joppen, Miriam Moneke, Nils Schröder, Christian Wirth and Johannes Fürnkranz, Informed Hybrid Game Tree Search, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD–KE–2016–01, 2016
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Christian Wirth, Johannes Fürnkranz and Gerhard Neumann, Model-Free Preference-based Reinforcement Learning, in: Proceedings of the 30th {AAAI} Conference on Artificial Intelligence (AAAI-16), Phoenix, Arizona, pages 2222--2228, 2016
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Sebastian Kauschke, Johannes Fürnkranz and Frederik Janssen, Predicting Cargo Train Failures: A Machine Learning Approach for a Lightweight Prototype, in: Proceedings of the 19th International Conference on Discovery Science (DS-16), Bari, Italy, pages 151--166, Springer-Verlag, 2016
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Markus Zopf, Eneldo Loza Mencía and Johannes Fürnkranz, Sequential Clustering and Contextual Importance Measures for Incremental Update Summarization, in: Proceedings of the 26th International Conference on Computational Linguistics, Osaka, Japan, pages 1071-1082, The COLING 2016 Organizing Committee, 2016
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Julius Stecher, Frederik Janssen and Johannes Fürnkranz, Shorter Rules Are Better, Aren't They?, in: Proceedings of the 19th International Conference on Discovery Science (DS-16), pages 279--294, Springer-Verlag, 2016
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Johannes Fürnkranz and Eyke Hüllermeier, Special Issue on Discovery Science (2016), in: Information Sciences, 329(849--850)
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Prateek Veeranna Sappadla, Jinseok Nam, Eneldo Loza Mencía and Johannes Fürnkranz, Using Semantic Similarity for Multi-Label Zero-Shot Classification of Text Documents, in: Proceedings of the 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN-16), d-side publications, 2016
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Fabian Hirschmann, Jinseok Nam and Johannes Fürnkranz, What Makes Word-level Neural Machine Translation Hard: A Case Study on English-German Translation, in: Proceedings of the 26th International Conference on Computational Linguistics (COLING-16), pages 3199--3208, ACL, 2016
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2015
Johannes Fürnkranz and Tomás Kliegr, A Brief Overview of Rule Learning, in: Rule Technologies: Foundations, Tools, and Applications -- Proceedings of the 9th International Symposium (RuleML-15), pages 54--69, Springer, 2015
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Johannes Fürnkranz, Editorial (2015), in: Data Mining and Knowledge Discovery, 29:1(1--2)
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Andrei Tolstikov, Frederik Janssen and Johannes Fürnkranz, Evaluation of different Regression Learners under Asymmetric Loss for Predictive Maintenance, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD–KE–2015–02, 2015
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Axel Schulz, Frederik Janssen, Petar Ristoski and Johannes Fürnkranz, Event-Based Clustering for Reducing Labeling Costs of Event-Related Microposts, in: Proceedings of the 9th International AAAI Conference on Web and Social Media (ICWSM-15), Oxford, UK, pages 686--690, AAAI Press, 2015
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Axel Schulz, Petar Ristoski, Johannes Fürnkranz and Frederik Janssen, Event-Based Clustering for Reducing Labeling Costs of Incident-Related Microposts, in: Proceedings of the ICML-15 2nd International Workshop on Mining Urban Data (MUD-15), Lille, France, pages 44--52, CEUR workshop proceedings, 2015
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Christian Wirth and Johannes Fürnkranz, On Learning from Game Annotations (2015), in: IEEE Transactions on Computational Intelligence and AI in Games, 7:3(304-316)
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Jinseok Nam, Eneldo Loza Mencía, Hyunwoo J. Kim and Johannes Fürnkranz, Predicting Unseen Labels using Label Hierarchies in Large-Scale Multi-label Learning, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, pages 102-118, Springer International Publishing, 2015
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2014
Christian Brinker, Eneldo Loza Mencía and Johannes Fürnkranz, Graded Multilabel Classification by Pairwise Comparisons, in: 2014 IEEE International Conference on Data Mining (ICDM 2014), pages 731--736, Curran Associates, IEEE, 2014
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Christian Brinker, Eneldo Loza Mencía and Johannes Fürnkranz, Graded Multilabel Classification by Pairwise Comparisons, Knowledge Engineering Group, Technische Universität Darmstadt, Technical Report, 2014
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Jinseok Nam, Jungi Kim, Eneldo Loza Mencía, Iryna Gurevych and Johannes Fürnkranz, Large-Scale Multi-label Text Classification - Revisiting Neural Networks, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD-14), Part 2, pages 437--452, Springer Berlin Heidelberg, 2014
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Christian Wirth and Johannes Fürnkranz, Preference Learning from Annotated Game Databases, in: Proceedings of the 16th {LWA} Workshops: KDML, {IR} and FGWM, pages 57--68, CEUR-WS.org, 2014
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Julius Stecher, Frederik Janssen and Johannes Fürnkranz, Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD-14), Part 3, pages 114--129, Springer, 2014
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2013
Christian Wirth and Johannes Fürnkranz, A Policy Iteration Algorithm for Learning from Preference-based Feedback, in: Advances in Intelligent Data Analysis XII: 12th International Symposium (IDA-13), pages 427--437, Springer-Verlag, 2013
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Eyke Hüllermeier and Johannes Fürnkranz, Editorial: Preference Learning and Ranking (2013), in: Machine Learning, 93:2-3(185--189)
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Christian Wirth and Johannes Fürnkranz, EPMC: Every Visit Preference Monte Carlo for Reinforcement Learning, in: Proceedings of the 5th Asian Conference on Machine Learning, (ACML-13), pages 483--497, JMLR.org, 2013
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Christian Wirth and Johannes Fürnkranz, Learning from Trajectory-Based Action Preferences, in: Proceedings of the ICRA 2013 Workshop on Autonomous Learning, Karslruhe, 2013
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Christian Wirth and Johannes Fürnkranz, Preference-Based Reinforcement Learning: A Preliminary Survey, in: Proceedings of the ECML/PKDD-13 Workshop on Reinforcement Learning from Generalized Feedback: Beyond Numeric Rewards, 2013
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Johannes Fürnkranz, Rule-Based Methods, in: Encyclopedia of Systems Biology, Springer-Verlag, 2013
Special Issue on Preference Learning and Ranking (2013), in: Machine Learning, 93:2-3
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2012
Lorenz Weizsäcker and Johannes Fürnkranz, Basic Instrument for Experimental Probes in Machine Learning, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD–KE–2012–01, 2012
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Sang-Hyeun Park and Johannes Fürnkranz, Efficient prediction algorithms for binary decomposition techniques (2012), in: Data Mining and Knowledge Discovery, 24:1(40-77)
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Johannes Fürnkranz and Sang-Hyeun Park, Error-Correcting Output Codes as a Transformation from Multi-Class to Multi-Label Prediction, in: Proceedings of the 15th International Conference on Discovery Science (DS-12), pages 254--267, Springer, 2012
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Christian Wirth and Johannes Fürnkranz, First Steps Towards Learning from Game Annotations, in: Proceedings of the {ECAI} Workshop on Preference Learning: Problems and Applications in AI, Montpellier, pages 53-58, 2012
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Wouter Duivesteijn, Eneldo Loza Mencía, Johannes Fürnkranz and Arno J. Knobbe, Multi-label LeGo -- Enhancing Multi-label Classifiers with Local Patterns, in: Advances in Intelligent Data Analysis XI -- Proceedings of the 11th International Symposium on Data Analysis (IDA-11), Berlin, pages 114--125, Springer, 2012
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Wouter Duivesteijn, Eneldo Loza Mencía, Johannes Fürnkranz and Arno J. Knobbe, Multi-label LeGo -- Enhancing Multi-label Classifiers with Local Patterns, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD-KE-2012-02, 2012
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Johannes Fürnkranz and Eyke Hüllermeier, Preference Learning, in: Encyclopedia of the Sciences of Learning, pages 986, Springer-Verlag, 2012
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Heiko Paulheim and Johannes Fürnkranz, Unsupervised Generation of Data Mining Features from Linked Open Data, in: International Conference on Web Intelligence and Semantics (WIMS'12), 2012
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2011
Frederik Janssen and Johannes Fürnkranz, Heuristic Rule-Based Regression via Dynamic Reduction to Classification, in: Proceedings of the 22nd International Joint Conference on Artificial Intelligence (IJCAI-11), Barcelona, Spain, pages 1330--1335, 2011
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Eyke Hüllermeier and Johannes Fürnkranz, Learning from Label Preferences, in: Proceedings of the 14th International Conference on Discovery Science (DS-11), pages 2--17, Springer, 2011
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Eyke Hüllermeier and Johannes Fürnkranz, Learning from Label Preferences, in: Proceedings of the 22nd International Conference on Algorithmic Learning Theory (ALT-11), pages 38, Springer, 2011
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Lorenz Weizsäcker and Johannes Fürnkranz, Margin Driven Separate and Conquer by Assymmetric Loss Functions, TU Darmstadt, Knowledge Engineering Group, number TUD–KE–2011–01, 2011
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Weiwei Cheng, Johannes Fürnkranz, Eyke Hüllermeier and Sang-Hyeun Park, Preference-Based Policy Iteration: Leveraging Preference Learning for Reinforcement Learning, in: Proceedings of the 22nd European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2011, Athens, Greece), Part I, pages 312--327, Springer, 2011
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Jan-Nikolas Sulzmann and Johannes Fürnkranz, Rule Stacking: An Approach for Compressing an Ensemble of Rule Sets into a Single Classifier, in: Proceedings of the 14th International Conference on Discovery Science (DS-11), pages 323--334, Springer, 2011
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Heiko Paulheim and Johannes Fürnkranz, Unsupervised Generation of Data Mining Features from Linked Open Data, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD-KE-2011-2, 2011
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2010
Philip Paulsen and Johannes Fürnkranz, A Moderately Successful Attempt to Train Chess Evaluation Functions of Different Strengths, in: Proceedings of the ICML-10 Workshop on Machine Learning and Games, 2010
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Johannes Fürnkranz, Decision List, in: Encyclopedia of Machine Learning, pages 261, Springer-Verlag, 2010
Johannes Fürnkranz, Decision Lists and Decision Trees, in: Encyclopedia of Machine Learning, pages 261--262, Springer-Verlag, 2010
Johannes Fürnkranz, Decision Tree, in: Encyclopedia of Machine Learning, pages 263--267, Springer-Verlag, 2010
Eneldo Loza Mencía and Johannes Fürnkranz, Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain, in: Semantic Processing of Legal Texts -- Where the Language of Law Meets the Law of Language, pages 192-215, Springer-Verlag, 2010
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Nada Lavrač, Johannes Fürnkranz and Dragan Gamberger, Explicit Feature Construction and Manipulation for Covering Rule Learning Algorithms, in: Advances in Machine Learning I --- Dedicated to the Memory of Professor Ryszard S. Michalski, pages 121--146, Springer-Verlag, 2010
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Sang-Hyeun Park, Lorenz Weizsäcker and Johannes Fürnkranz, Exploiting Code Redundancies in ECOC, in: Proceedings of the 13th International Conference on Discovery Science (DS-10), pages 266--280, Springer, 2010
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Johannes Fürnkranz and Arno J. Knobbe, Guest Editorial: Global Modeling using Local Patterns (2010), in: Data Mining and Knowledge Discovery, 21:1(1--8)
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Marco Ghiglieri and Johannes Fürnkranz, Learning to Recognize Missing E-mail Attachments (2010), in: Applied Artificial Intelligence, 24:5(443-462)
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Johannes Fürnkranz, Machine Learning and Game Playing, in: Encyclopedia of Machine Learning, pages 633--637, Springer-Verlag, 2010
Eyke Hüllermeier and Johannes Fürnkranz, On Predictive Accuracy and Risk Minimization in Pairwise Label Ranking (2010), in: Journal of Computer and System Sciences, 76:1(49--62)
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Johannes Fürnkranz and Eyke Hüllermeier, Preference Learning, in: Encyclopedia of Machine Learning, pages 789--795, Springer-Verlag, 2010
Preference Learning, Springer-Verlag, 2010
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Johannes Fürnkranz and Eyke Hüllermeier, Preference Learning and Ranking by Pairwise Comparison, in: Preference Learning, pages 65--82, Springer-Verlag, 2010
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Johannes Fürnkranz and Eyke Hüllermeier, Preference Learning: An Introduction, in: Preference Learning, pages 1--17, Springer-Verlag, 2010
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Jan-Nikolas Sulzmann and Johannes Fürnkranz, Probability Estimation and Aggregation for Rule Learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-03, 2010
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Jan-Nikolas Sulzmann and Johannes Fürnkranz, Probability Estimation and Aggregation for Rule Learning, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2010, Kassel, Germany, pages 143--150, 2010
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Johannes Fürnkranz, Pruning, in: Encyclopedia of Machine Learning, pages 817, Springer-Verlag, 2010
Johannes Fürnkranz, Rule Learning, in: Encyclopedia of Machine Learning, pages 875--879, Springer-Verlag, 2010
Frederik Janssen and Johannes Fürnkranz, Separate-and-conquer Regression, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-01, 2010
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Frederik Janssen and Johannes Fürnkranz, Separate-and-conquer Regression, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2010, Kassel, Germany, pages 81--89, 2010
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Frederik Janssen and Johannes Fürnkranz, The SeCo-framework for rule learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-02, 2010
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Johannes Fürnkranz, Web Mining, in: Data Mining and Knowledge Discovery Handbook, pages 913--930, Springer-Verlag, 2010
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2009
Lars Wohlrab and Johannes Fürnkranz, A Comparison of Strategies for Handling Missing Values in Rule Learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2009-03, 2009
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Frederik Janssen and Johannes Fürnkranz, A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning, in: Proceedings of the SIAM International Conference on Data Mining (SDM-09), pages 329--340, 2009
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Jan-Nikolas Sulzmann and Johannes Fürnkranz, A Study of Probability Estimation Techniques for Rule Learning, in: From Local Patterns to Global Models: Proceedings of the ECML/PKDD-09 Workshop (LeGo-09), pages 123--138, 2009
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Jan-Nikolas Sulzmann and Johannes Fürnkranz, An Empirical Comparison of Probability Estimation Techniques for Probabilistic Rules, in: Proceedings of the 12th International Conference on Discovery Science (DS-09), Porto, Portugal, pages 317--331, Springer-Verlag, 2009
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Immanuel Schweizer, Kamill Panitzek, Sang-Hyeun Park and Johannes Fürnkranz, An Exploitative Monte-Carlo Poker Agent, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2009-02, 2009
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Immanuel Schweizer, Kamill Panitzek, Sang-Hyeun Park and Johannes Fürnkranz, An Exploitative Monte-Carlo Poker Agent, in: Proceedings of the 32nd Annual German Conference on Artificial Intelligence (KI 2009, Paderborn, Germany), pages 65--72, Springer, 2009
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Immanuel Schweizer, Kamill Panitzek, Sang-Hyeun Park and Johannes Fürnkranz, An Exploitative Monte-Carlo Poker Agent, in: Proceedings of the LWA 2009: Lernen -- Wissen -- Adaption, Workshop Knowledge Discovery, Data Mining and Machine Learning (KDML-09), pages 100--104, 2009
Johannes Fürnkranz, Eyke Hüllermeier and Stijn Vanderlooy, Binary Decomposition Methods for Multipartite Ranking, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD-09), pages 359--374, Springer-Verlag, 2009
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Sang-Hyeun Park and Johannes Fürnkranz, Efficient Decoding of Ternary Error-Correcting Output Codes for Multiclass Classification, in: Proceedings of the 20th European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2009, Bled, Slovenia), Part II, pages 189--204, Springer, 2009
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Eneldo Loza Mencía, Sang-Hyeun Park and Johannes Fürnkranz, Efficient Voting Prediction for Pairwise Multilabel Classification, in: Proceedings of the 17th European Symposium on Artificial Neural Networks (ESANN 2009, Bruges, Belgium), pages 117--122, d-side publications, 2009
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Eneldo Loza Mencía, Sang-Hyeun Park and Johannes Fürnkranz, Efficient Voting Prediction for Pairwise Multilabel Classification, in: Proceedings of the LWA 2009: Lernen - Wissen - Adaption, Workshop Knowledge Discovery, Data Mining and Machine Learning (KDML-09), Darmstadt, Germany, pages 72--75, 2009
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Marco Ghiglieri and Johannes Fürnkranz, Learning To Recognize Missing E-mail Attachments, Knowledge Engineering Group, TU Darmstadt, number TUD-KE-2009-05, 2009
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Lorenz Weizsäcker and Johannes Fürnkranz, Margin Driven Separate and Conquer by Working Set Expansion, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2009-06, 2009
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Lorenz Weizsäcker and Johannes Fürnkranz, On Table Extraction from Text Sources with Markups, in: Proceedings of the LWA 2009: Lernen -- Wissen -- Adaption, Workshop Information Retrieval (WIR-09), pages 1--8, 2009
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Grigorios Tsoumakas, Eneldo Loza Mencía, Ioannis Katakis, Sang-Hyeun Park and Johannes Fürnkranz, On the Combination of Two Decompositive Multi-Label Classification Methods, in: Proceedings of the ECML PKDD 2009 Workshop on Preference Learning (PL-09, Bled, Slovenia), pages 114--129, 2009
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2008
Jan-Nikolas Sulzmann and Johannes Fürnkranz, A Comparison of Techniques for Selecting and Combining Class Association Rules, in: From Local Patterns to Global Models: Proceedings of the ECML/PKDD-08 Workshop (LeGo-08), pages 154--168, 2008
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Jan-Nikolas Sulzmann and Johannes Fürnkranz, A Comparison of Techniques for Selecting and Combining Class Association Rules, in: Proceedings of the LWA 2008: Lernen -- Wissen -- Adaption, pages "", 2008
Frederik Janssen and Johannes Fürnkranz, A Re-Evaluation of the Over-Searching Phenomenon in Inductive Rule Learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-02, 2008
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Frederik Janssen and Johannes Fürnkranz, A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2008, pages 42-50, 2008
Eneldo Loza Mencía, Sang-Hyeun Park and Johannes Fürnkranz, Advances in Efficient Pairwise Multilabel Classification, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-06, 2008
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Frederik Janssen and Johannes Fürnkranz, An Empirical Investigation of the Trade-Off between Consistency and Coverage in Rule Learning Heuristics, in: Proceedings of the 11th International Conference on Discovery Science (DS-08), pages 40--51, Springer-Verlag, 2008
[DOI]
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Frederik Janssen and Johannes Fürnkranz, An Empirical Quest for Optimal Rule Learning Heuristics, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-01, 2008
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Eneldo Loza Mencía and Johannes Fürnkranz, An Evaluation of Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain, in: Proceedings of the LREC 2008 Workshop on Semantic Processing of Legal Texts, pages 23-32, 2008
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Eneldo Loza Mencía and Johannes Fürnkranz, Efficient Pairwise Multilabel Classification for Large-Scale Problems in the Legal Domain, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Disocvery in Databases (ECML-PKDD-2008), Part II, pages 50--65, Springer, 2008
[DOI]
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Arno J. Knobbe, Bruno Crémilleux, Johannes Fürnkranz and Martin Scholz, From Local Patterns to Global Models: The LeGo Approach to Data Mining, in: From Local Patterns to Global Models: Proceedings of the ECML/PKDD-08 Workshop (LeGo-08), pages 1--16, 2008
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Dragan Gamberger, Nada Lavrač and Johannes Fürnkranz, Handling Unknown and Imprecise Attribute Values in Propositional Rule Learning: A Feature-Based Approach, in: Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence (PRICAI-08), pages 636--645, Springer-Verlag, 2008
Eyke Hüllermeier, Johannes Fürnkranz, Weiwei Cheng and Klaus Brinker, Label Ranking by Learning Pairwise Preferences (2008), in: Artificial Intelligence, 172:16–17(1897--1916)
[DOI]
Sacha Droste and Johannes Fürnkranz, Learning of Piece Values for Chess Variants, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-07, 2008
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Eyke Hüllermeier and Johannes Fürnkranz, Learning Preference Models from Data: On the Problem of Label Ranking and Its Variants, in: Preferences and Similarities, pages 283--304, Springer-Verlag, 2008
[DOI]
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Sacha Droste and Johannes Fürnkranz, Learning the Piece Values for Three Chess Variants (2008), in: International Computer Games Association Journal, 31:4(209--233)
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Sang-Hyeun Park and Johannes Fürnkranz, Multi-Label Classification with Label Constraints, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-04, 2008
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Sang-Hyeun Park and Johannes Fürnkranz, Multi-Label Classification with Label Constraints, in: Proceedings of the ECML PKDD 2008 Workshop on Preference Learning (PL-08, Antwerp, Belgium), pages 157--171, 2008
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Lorenz Weizsäcker and Johannes Fürnkranz, On Table Extraction from Text Sources with Markups, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-05, 2008
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Eneldo Loza Mencía and Johannes Fürnkranz, Pairwise Learning of Multilabel Classifications with Perceptrons, in: Proceedings of the 2008 IEEE International Joint Conference on Neural Networks (IJCNN-08), IEEE, pages 2900--2907, 2008
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2007
Sang-Hyeun Park and Johannes Fürnkranz, Efficient Pairwise Classification, in: Proceedings of the 18th European Conference on Machine Learning (ECML 2007, Warsaw, Poland), pages 658--665, Springer-Verlag, 2007
[DOI]
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Sang-Hyeun Park and Johannes Fürnkranz, Efficient Pairwise Classification and Ranking, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-03, 2007
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Klaus Brinker, Johannes Fürnkranz and Eyke Hüllermeier, Label Ranking by Learning Pairwise Preferences, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-01, 2007
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Frederik Janssen and Johannes Fürnkranz, Meta-Learning Rule Learning Heuristics, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-02, 2007
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Frederik Janssen and Johannes Fürnkranz, Meta-Learning Rule Learning Heuristics, in: Proceedings of ECML-PKDD-07 Workshop on Planning to Learn (PlanLearn-07), pages 9-21, 2007
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Frederik Janssen and Johannes Fürnkranz, Meta-Learning Rule Learning Heuristics, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2007, pages 167--174, 2007
Frederik Janssen and Johannes Fürnkranz, On Meta-Learning Rule Learning Heuristics, in: Proceedings of the 7th IEEE International Conference on Data Mining (ICDM-07), pages 529--534, 2007
[DOI]
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Eyke Hüllermeier and Johannes Fürnkranz, On Minimizing the Position Error in Label Ranking, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-04, 2007
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Eyke Hüllermeier and Johannes Fürnkranz, On Minimizing the Position Error in Label Ranking, in: Proceedings of 18th European Conference on Machine Learning (ECML-07), pages 583--590, Springer-Verlag, 2007
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Jan-Nikolas Sulzmann, Johannes Fürnkranz and Eyke Hüllermeier, On Pairwise Naive Bayes Classifiers, in: Proceedings of 18th European Conference on Machine Learning (ECML-07), pages 371--381, Springer-Verlag, 2007
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Eneldo Loza Mencía and Johannes Fürnkranz, Pairwise Learning of Multilabel Classifications with Perceptrons, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-05, 2007
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2006
Klaus Brinker, Johannes Fürnkranz and Eyke Hüllermeier, A Unified Model for Multilabel Classification and Ranking, in: Proceedings of the 17th European Conference on Artificial Intelligence (ECAI-06), pages 489--493, 2006
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Klaus Brinker and Eyke Hüllermeier, Case-Based Label Ranking, in: Proceedings of the 17th European Conference on Machine Learning (ECML-06), pages 566--573, Springer-Verlag, 2006
Bin Wang and Harry Zhang, Improving the Ranking Performance of Decision Trees, in: Proceedings of the 17th European Conference on Machine Learning (ECML-06), pages 461--472, Springer-Verlag, 2006
Hervé Utard and Johannes Fürnkranz, Link-local Features for Hypertext Classification, in: Semantics, Web and Mining, pages 51--64, Springer-Verlag, 2006
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Machine Learning: ECML 2006, Springer-Verlag, 2006
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Daniel Druckman, Richard Harris and Johannes Fürnkranz, Modeling International Negotiation: Statistical and Machine Learning Approaches, in: Programming for Peace: Computer-Aided Methods for International Conflict Resolution and Prevention, pages 227--250, Kluwer Academic Publishers, 2006
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Frederik Janssen and Johannes Fürnkranz, On Trading Off Consistency and Coverage in Inductive Rule Learning, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2006, pages 306--313, Gesellschaft für Informatik e. V. (GI), 2006
[URL]
Arno J. Knobbe and Eric K. Y. Ho, Pattern Teams, in: Proceedings of the 10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD-06), pages 577--584, Springer-Verlag, 2006
[DOI]
2005
Johannes Fürnkranz, From Local to Global Patterns: Evaluation Issues in Rule Learning Algorithms, in: Local Pattern Detection, pages 20--38, Springer-Verlag, 2005
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Eyke Hüllermeier and Johannes Fürnkranz, Learning Label Preferences: Ranking Error versus Position Error, in: Advances in Intelligent Data Analysis: Proceedings of the 6th International Symposium (IDA-05), pages 180--191, Springer-Verlag, 2005
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Hervé Utard and Johannes Fürnkranz, Link-local Features for Hypertext Classification, in: Proceedings of the European Web Mining Forum (EWMF-05): Workshop at ECML/PKDD-05, pages 40--51, 2005
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LWA 2005, Lernen Wissensentdeckung Adaptivität, German Research Center for Artificial Intelligence (DFKI), 2005
[URL]
Bernhard Pfahringer, Geoffrey Holmes and C. Wang, Millions of Random Rules, in: Proceedings of the ECML/PKDD Workshop on Advances in Inductive Rule Learning, 2005
Eyke Hüllermeier, Johannes Fürnkranz and Jürgen Beringer, On Position Error and Label Ranking through Iterated Choice, in: {LWA 2005, Lernen Wissensentdeckung Adaptivität}, pages 158--163, German Research Center for Artificial Intelligence (DFKI), 2005
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Johannes Fürnkranz and Eyke Hüllermeier, Preference Learning (2005), in: Künstliche Intelligenz, 19:1(60--61)
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Johannes Fürnkranz, Web Mining, in: Data Mining and Knowledge Discovery Handbook, pages 899--920, Springer-Verlag, 2005
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2004
Johannes Fürnkranz and Peter A. Flach, An Analysis of Stopping and Filtering Criteria for Rule Learning, in: Proceedings of the 15th European Conference on Machine Learning (ECML-04), pages 123--133, Springer-Verlag, 2004
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Eyke Hüllermeier and Johannes Fürnkranz, Comparison of Ranking Procedures in Pairwise Preference Learning, in: Proceedings of the 10th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU-04), 2004
[URL]
Johannes Fürnkranz, Modeling Rule Precision, in: Lernen -- Wissensentdeckung --- Adaptivität. Proceedings of the LWA-04 Workshops, pages 147--154, 2004
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Johannes Fürnkranz, Modeling Rule Precision, in: Proceedings of the ECML/PKDD-04 Workshop on Advances in Inductive Rule Learning, pages 30--45, 2004
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Eyke Hüllermeier and Johannes Fürnkranz, Ranking by Pairwise Comparison: A Note on Risk Minimization, in: Proceedings of the IEEE International Conference on Fuzzy Systems (FUZZ-IEEE-04), 2004
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2003
Johannes Fürnkranz and Peter A. Flach, An Analysis of Rule Evaluation Metrics, in: Proceedings of the 20th International Conference on Machine Learning (ICML-03), pages 202--209, AAAI Press, 2003
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Johannes Fürnkranz and Peter A. Flach, An Analysis of Rule Learning Heuristics, Department of Computer Science, University of Bristol, number CSTR-03-002, 2003
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Petr Savicky and Johannes Fürnkranz, Combining Pairwise Classifiers with Stacking, in: Advances in Intelligent Data Analysis: Proceedings of the 5th International Symposium (IDA-03), pages 219--229, Springer-Verlag, 2003
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Johannes Fürnkranz, Modeling Rule Precision, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2003-35, 2003
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Francesco C. Billari, Alexia Prskawetz and Johannes Fürnkranz, On the Cultural Evoluation of Age-at-marriage Norms, in: Agent-Based Computational Demography, pages 139--157, Physica-Verlag / Springer, 2003
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Johannes Fürnkranz and Eyke Hüllermeier, Pairwise Preference Learning and Ranking, in: Proceedings of the 14th European Conference on Machine Learning (ECML-03), pages 145--156, Springer-Verlag, 2003
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Johannes Fürnkranz and Eyke Hüllermeier, Pairwise Preference Learning and Ranking, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2003-14, 2003
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Johannes Fürnkranz and Eyke Hüllermeier, Pairwise Preference Learning and Ranking, in: Preference Learning: Models, Methods, Applications -- Proceedings of the KI-2003 Workshop, 2003
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Preference Learning: Models, Methods, Applications -- Proceedings of the KI-2003 Workshop, Austrian Research Institute for Artificial Intelligence, 2003
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Johannes Fürnkranz, Round Robin Ensembles (2003), in: Intelligent Data Analysis, 7:5(385--404)
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2002
Johannes Fürnkranz, A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-28, 2002
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Johannes Fürnkranz, A Pathology of Bottom-Up Hill-Climbing in Inductive Rule Learning, in: Proceedings of the 13th European Conference on Algorithmic Learning Theory (ALT-02), pages 263--277, Springer-Verlag, 2002
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Johannes Fürnkranz, Johann Petrak, Pavel B. Brazdil and Carlos Soares, On the Use of Fast Subsampling Estimates for Algorithm Recommendation, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-36, 2002
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Johannes Fürnkranz, Pairwise Classification as an Ensemble Technique, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-20, 2002
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Johannes Fürnkranz, Pairwise Classification as an Ensemble Technique, in: Proceedings of the 13th European Conference on Machine Learning (ECML-02), pages 97--110, Springer-Verlag, 2002
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Johannes Fürnkranz, Round Robin Classification (2002), in: Journal of Machine Learning Research, 2(721--747)
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Johannes Fürnkranz, Round Robin Ensembles, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-37, 2002
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Johannes Fürnkranz, Christian Holzbaur and Robert Temel, User Profiling for the Melvil Knowledge Retrieval System (2002), in: Applied Artificial Intelligence, 16:4(243--281)
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Johannes Fürnkranz, Web Structure Mining --- Exploiting the Graph Structure of the World-Wide Web, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2002-33, 2002
[URL]
2001
Alexander K. Seewald and Johannes Fürnkranz, An Evaluation of Grading Classifiers, in: Advances in Intelligent Data Analysis: Proceedings of the 4th International Conference (IDA-01), pages 115--124, Springer-Verlag, 2001
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Johannes Fürnkranz and Johann Petrak, An Evaluation of Landmarking Variants, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-13, 2001
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Johannes Fürnkranz and Johann Petrak, An Evaluation of Landmarking Variants, in: Proceedings of the ECML/PKDD Workshop on Integrating Aspects of Data Mining, Decision Support and Meta-Learning (IDDM-2001), pages 57--68, 2001
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Hendrik Blockeel, Johannes Fürnkranz, Alexia Prskawetz and Francesco C. Billari, Detecting Temporal Change in Event Sequences: An Application to Demographic Data, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-09, 2001
[URL]
Hendrik Blockeel, Johannes Fürnkranz, Alexia Prskawetz and Francesco C. Billari, Detecting Temporal Change in Event Sequences: An Application to Demographic Data, in: Proceedings of the 5th European Conference on Principles of Data Mining and Knowledge Discovery (PKDD-01), pages 29--41, Springer-Verlag, 2001
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Alexander K. Seewald and Johannes Fürnkranz, Grading Classifiers, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-01, 2001
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Johannes Fürnkranz, Hyperlink Ensembles: A Case Study in Hypertext Classification, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-30, 2001
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Johannes Fürnkranz, Inductive Rule Learning for Data and Web Mining, Habilitationsschrift, Technisch-Naturwissenschaftliche Fakult{\"a}t, Technische Universi{\"a}t Wien, 2001
Johannes Fürnkranz, Machine Learning in Games: A Survey, in: Machines that Learn to Play Games, pages 11--59, Nova Science Publishers, 2001
[URL]
Machines that Learn to Play Games, Nova Science Publishers, Advances in Computation: Theory and Practice, volume 8, 2001
[URL]
Johannes Fürnkranz, Round Robin Classification, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-18, 2001
[URL]
Johannes Fürnkranz, Round Robin Rule Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-02, 2001
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Johannes Fürnkranz, Round Robin Rule Learning, in: Proceedings of the 18th International Conference on Machine Learning (ICML-01), pages 146--153, Morgan Kaufmann Publishers, 2001
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Johannes Fürnkranz, Christian Holzbaur and Robert Temel, User Profiling for the Melvil Knowledge Retrieval System, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2001-29, 2001
[URL]
2000
Johannes Fürnkranz, Bernhard Pfahringer, Hermann Kaindl and Stefan Kramer, Learning to Use Operational Advice, in: Proceedings of the 14th European Conference on Artificial Intelligence (ECAI-00), pages 291--295, IOS Press, 2000
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Johannes Fürnkranz, Machine Learning in Games: A Survey, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2000-31, 2000
[URL]
Francesco C. Billari, Johannes Fürnkranz and Alexia Prskawetz, Timing, Sequencing, and Quantum of Life Course Events: A Machine Learning Approach, Max Planck Institute for Demographic Research, number WP 2000-010, MPIDR Working Paper, 2000
[URL]
Francesco C. Billari, Johannes Fürnkranz and Alexia Prskawetz, Timing, Sequencing, and Quantum of Life Course Events: A Machine Learning Approach, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-2000-30, 2000
[URL]
1999
Johannes Fürnkranz, Exploiting Structural Information for Text Classification on the WWW, in: Advances in Intelligent Data Analysis: Proceedings of the 3rd International Symposium (IDA-99), pages 487--497, Springer-Verlag, 1999
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Bernhard Pfahringer, Hermann Kaindl, Stefan Kramer and Johannes Fürnkranz, Learning to Make Good Use of Operational Advice, in: Proceedings of the ICML-99 Workshop on Machine Learning in Game Playing, 1999
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Johannes Fürnkranz, Separate-and-Conquer Rule Learning (1999), in: Artificial Intelligence Review, 13:1(3--54)
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Johannes Fürnkranz and Miroslav Kubat, Workshop Report: Machine Learning in Game Playing (1999), in: International Computer Chess Association Journal, 22:3(178,179,165)
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1998
Johannes Fürnkranz, Tom M. Mitchell and Ellen Riloff, A Case Study in Using Linguistic Phrases for Text Categorization on the WWW, in: Learning for Text Categorization: Proceedings of the 1998 AAAI/ICML Workshop, pages 5--12, AAAI Press, 1998
[URL]
Franz-Günter Winkler and Johannes Fürnkranz, A Hypothesis on the Divergence of AI Research (1998), in: International Computer Chess Association Journal, 21:1(3--13)
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Johannes Fürnkranz, A Study Using $n$-gram Features for Text Categorization, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-98-30, 1998
[URL]
Johannes Fürnkranz and Bernhard Pfahringer, Guest Editorial: First-Order Knowledge Discovery in Databases (1998), in: Applied Artificial Intelligence, 12:5(345--361)
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Johannes Fürnkranz, Integrative Windowing (1998), in: Journal of Artificial Intelligence Research, 8(129--164)
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Johannes Fürnkranz, Using Links for Classifying Web-Pages, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-98-29, 1998
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1997
Johannes Fürnkranz, Bericht über IJCAI-97 und AAAI-97 (1997), in: ÖGAI--Journal, 16:3(30--33)
Johannes Fürnkranz, Dimensionality Reduction in ILP: A Call to Arms, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-97-26, 1997
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Johannes Fürnkranz, Dimensionality Reduction in ILP: A Call to Arms, in: Proceedings of the IJCAI-97 Workshop on Frontiers of Inductive Logic Programming, pages 81--86, 1997
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Johannes Fürnkranz, Knowledge Discovery in Chess Databases: A Research Proposal, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-97-33, 1997
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Johannes Fürnkranz, Johann Petrak and Robert Trappl, Knowledge Discovery in International Conflict Databases (1997), in: Applied Artificial Intelligence, 11:2(91--118)
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Robert Trappl, Johannes Fürnkranz, Johann Petrak and Jacob Bercovitch, Machine Learning and Case-based Reasoning: Their Potential Role in Preventing the Outbreak of Wars or in Ending Them, in: Learning, Networks and Statistics: Proceedings of the ISSEK-96 Workshop, pages 209--225, Springer-Verlag, 1997
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Johannes Fürnkranz, More Efficient Windowing, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-97-01, 1997
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Johannes Fürnkranz, More Efficient Windowing, in: Proceedings of the 14th National Conference on Artificial Intelligence (AAAI-97), pages 509-514, AAAI Press, 1997
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Johannes Fürnkranz, Noise-Tolerant Windowing, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-97-07, 1997
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Johannes Fürnkranz, Noise-Tolerant Windowing, in: Proceedings of the 15th International Joint Conference on Artificial Intelligence (IJCAI-97), pages 852--857, Morgan Kaufmann, 1997
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Franz-Günter Winkler and Johannes Fürnkranz, On Effort in AI Research: A Description Along Two Dimensions, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-97-25, 1997
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Franz-Günter Winkler and Johannes Fürnkranz, On Effort in AI Research: A Description Along Two Dimensions, in: Deep Blue Versus Kasparov: The Significance for Artificial Intelligence: Papers from the 1997 AAAI Workshop, pages 56--62, AAAI Press, 1997
[URL]
Johannes Fürnkranz, Pruning Algorithms for Rule Learning (1997), in: Machine Learning, 27:2(139--171)
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1996
Uroš Pompe, Igor Kononenko and T. Makse, An application of ILP in a Musical Database: Learning to Compose the Two-Voice Counterpoint, in: Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programming (ILP for KDD), 1996
David Lorenzo, Application of Clausal Discovery to Temporal Databases, in: Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programming, pages 25--40, 1996
Johannes Fürnkranz, Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-96-10, 1996
[URL]
Robert Trappl, Johannes Fürnkranz and Johann Petrak, Digging for Peace: Using Machine Learning Methods for Assessing International Conflict Databases, in: Proceedings of the 12th European Conference on Artificial Intelligence (ECAI-96), pages 453--457, John Wiley \& Sons, 1996
[URL]
Peter Brockhausen and Katharina Morik, Direct Access of an ILP Algorithm to a Database Management System, in: Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programming, pages 95--110, 1996
Johannes Fürnkranz, Johann Petrak and Robert Trappl, Knowledge Discovery in International Conflict Databases, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-96-24, 1996
Johannes Fürnkranz, Machine Learning in Computer Chess: The Next Generation, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-96-11, 1996
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Johannes Fürnkranz, Machine Learning in Computer Chess: The Next Generation (1996), in: International Computer Chess Association Journal, 19:3(147--161)
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Johannes Fürnkranz, Pruning Algorithms for Rule Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-96-07, 1996
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Hendrik Blockeel and Luc De Raedt, Relational Knowledge Discovery in Databases, in: Proceedings of the MLnet Familiarization Workshop on Data Mining with Inductive Logic Programming, pages 111--124, 1996
Johannes Fürnkranz, Separate-and-Conquer Rule Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-96-25, 1996
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1995--2000
1995
Johannes Fürnkranz, A Tight Integration of Pruning and Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-95-03, 1995
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Johannes Fürnkranz, A Tight Integration of Pruning and Learning (Extended Abstract), in: Proceedings of the 8th European Conference on Machine Learning (ECML-95), pages 291--294, Springer-Verlag, 1995
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1994
Johannes Fürnkranz, A Comparison of Pruning Methods for Relational Concept Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-94-16, 1994
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Johannes Fürnkranz, A Comparison of Pruning Methods for Relational Concept Learning, in: Knowledge Discovery in Databases: Papers from the 1994 AAAI Workshop (KDD-94), pages 371--382, AAAI Press, 1994
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Johannes Fürnkranz and Gerhard Widmer, Incremental Reduced Error Pruning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-94-09, 1994
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Johannes Fürnkranz and Gerhard Widmer, Incremental Reduced Error Pruning, in: Proceedings of the 11th International Conference on Machine Learning (ML-94), pages 70--77, Morgan Kaufmann, 1994
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Johannes Fürnkranz, Pruning Methods for Rule Learning Algorithms, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-94-26, 1994
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Johannes Fürnkranz, Pruning Methods for Rule Learning Algorithms, in: Proceedings of the 4th International Workshop on Inductive Logic Programming (ILP-94), pages 321--336, 1994
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Johannes Fürnkranz, Top-Down Pruning in Relational Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-94-03, 1994
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Johannes Fürnkranz, Top-Down Pruning in Relational Learning, in: Proceedings of the 11th European Conference on Artificial Intelligence (ECAI-94), pages 453--457, John Wiley \& Sons, 1994
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Johannes Fürnkranz, {\sc Fossil}: {A} Robust Relational Learner, in: Proceedings of the 7th European Conference on Machine Learning (ECML-94), pages 122--137, Springer-Verlag, 1994
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1993
Johannes Fürnkranz, Application of Machine Learning Methods to the KOSIMO Database, Paper presented at the International Workshop on the Potential Contribution of Artificial Intelligence to the Avoidance of Crises and Wars, Vienna, 1993
Johannes Fürnkranz, Avoiding Noise Fitting in a {\sc Foil}-like Learning Algorithm, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-93-16, 1993
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Johannes Fürnkranz, Avoiding Noise Fitting in a {\sc Foil}-like Learning Algorithm, in: Proceedings of the IJCAI-93 Workshop on Inductive Logic Programming, pages 14--23, 1993
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Johannes Fürnkranz, The Role of Qualitative Knowledge in Machine Learning, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-93-09, 1993
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Johannes Fürnkranz, {\sc Fossil}: {A} robust relational learner, Austrian Research Institute for Artificial Intelligence, number OEFAI-TR-93-28, 1993
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1991
1990