Publications for topic "Projects"
2017
2016
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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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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Markus Zopf, Maxime Peyrard and Judith Eckle{-}Kohler, The Next Step for Multi-Document Summarization: A Heterogeneous Multi-Genre Corpus Built with a Novel Construction Approach, in: Proceedings of the 26th International Conference on Computational Linguistics, Osaka, Japan, pages 1535-1545, The COLING 2016 Organizing Committee, 2016
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2015
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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Sebastian Kauschke, Frederik Janssen and Immanuel Schweizer, On the Challenges of Real World Data in Predictive Maintenance Scenarios: A Railway Application, in: Proceedings of the LWA 2015 Workshops: KDML, FGWM, IR, and FGDB, Trier, Germany, October 7-9, 2015., pages 121-132, CEUR Workshop Proceedings, 2015
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Markus Zopf, SeqCluSum: Combining Sequential Clustering and Contextual Importance Measuring to Summarize Developing Events over Time, in: The Twenty-Fourth Text Retrieval Conference Proceedings, Gaithersburg, Maryland, USA, National Institute of Standards and Technology, 2015
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2014
Petar Ristoski, Eneldo Loza Mencía and Heiko Paulheim, A Hybrid Multi-Strategy Recommender System Using Linked Open Data, in: Semantic Web Evaluation Challenge, Proceedings (ESWC 2014), pages 150-156, Springer, 2014
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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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Sebastian Kauschke, Immanuel Schweizer, Michael Fiebrig and Frederik Janssen, Learning to Predict Component Failures in Trains, in: Proceedings of the 16th LWA Workshops: KDML, IR and FGWM, pages 71--82, CEUR Workshop Proceedings, 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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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
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
Ji-Ung Lee, Transductive Pairwise Classification, TU Darmstadt, Knowledge Engineeering Group, 2013
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Victor-Philipp Negoescu, Wissensgewinn aus Spieldatenbanken, Knowledge Engineering Group, TU Darmstadt, 2013
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2012
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, 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
Frederik Janssen, Faraz Fallahi, Jan Noessner and Heiko Paulheim, Towards Rule Learning Approaches to Instance-based Ontology Matching, in: 1st International Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data (Know@LOD), pages 13--18, 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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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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2010
Eneldo Loza Mencía, An Evaluation of Multilabel Classification for the Automatic Annotation of Texts, in: Proceedings of the LWA 2010: Lernen, Wissen, Adaptivität, Workshop on Knowledge Discovery, Data Mining and Machine Learning (KDML 2010), Kassel, pages 121-123, 2010
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Anne-Christine Karpf, Bidirectional Rule Learning, Knowledge Engineering Group, TU Darmstadt, 2010
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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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Jiawei Du, Iterative Optimization of Rule Sets, TU Darmstadt, Knowledge Engineering Group, 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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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, The SeCo-framework for rule learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-02, 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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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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Aleksandrs Galickis, Informationsextraktion aus Lebensläufen, TU Darmstadt, Knowledge Engineering Group, 2009
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Matthias Beckerle, Interaktives Regellernen, TU Darmstadt, Knowledge Engineering Group, 2009
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Eneldo Loza Mencía, Segmentation of legal documents, in: Proceedings of the 12th International Conference on Artificial Intelligence and Law, Barcelona, Spain, pages 88--97, ACM, 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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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
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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
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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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Jan Frederik Sima, Paarweise Hierarchische Klassifikation, TU Darmstadt, Knowledge Engineering Group, 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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Sven Wagner, Supervised Local Pattern Discovery, TU Darmstadt, Knowledge Engineering Group, 2008
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Benedict Werling, Vergleich von Pruning-Algorithmen für Regel-Lerner, TU Darmstadt, Knowledge Engineering Group, 2008
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2007
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
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
Jun Ying, Analysis and Comparison of Existent Information Extraction Methods, TU Darmstadt, Knowledge Engineering Group, 2006
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Sven Burges, Meta-Lernen einer Evaluierungs-Funktion für einen Regel-Lerner, TU Darmstadt, Knowledge Engineering Group, 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
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Marc Ruppert, Vergleich von AQ, CN2 und CN2 mit Weighted Covering, TU Darmstadt, Knowledge Engineering Group, 2006
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