Frederik Janssen
First name(s): Frederik
Last name(s): Janssen

Publications of Frederik Janssen
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), Springer-Verlag, 2017
2016
Big Data Analytics in the Social and Ubiquitous Context, Springer, Lecture Notes in Computer Science, volume 9546, 2016
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Jan Ruben Zilke, Eneldo Loza Mencía and Frederik Janssen, DeepRED -- Rule Extraction from Deep Neural Networks, in: Discovery Science: 19th International Conference, DS 2016, Bari, Italy, October 19--21, 2016, Proceedings, pages 457--473, Springer International Publishing, 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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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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Christian Meurisch, Usman Naeem, Muhammad Awais Azam, Frederik Janssen, Benedikt Schmidt and Max Mühlhäuser, Smarticipation: intelligent personal guidance of human behavior utilizing anticipatory models, in: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp Adjunct 2016, Heidelberg, Germany, pages 1227--1230, 2016
2015
Axel Schulz, Jakob Karolus, Frederik Janssen and Immanuel Schweizer, Accurate Pollutant Modeling and Mapping: Applying Machine Learning to Participatory Sensing and Urban Topology Data, in: Proceedings of the International Conference on Networked Systems (NetSys2015), Cottbus, Germany, pages 1--8, IEEE, 2015
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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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Heiko Paulheim, Axel Schulz, Frederik Janssen, Petar Ristoski and Immanuel Schweizer, Intelligente Datenauswertung mit Linked Open Data, in: Corporate Semantic Web: Wie semantische Anwendungen in Unternehmen Nutzen stiften, pages 187--201, Springer Vieweg, 2015
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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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2014
Timo Nolle, Immanuel Schweizer and Frederik Janssen, Data-driven Detection of Congestion-affected Roads, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD–KE–2014–02, 2014
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Alexander Gabriel, Heiko Paulheim and Frederik Janssen, Learning Semantically Coherent Rules, in: Proceedings of the 1st International Workshop on Interactions between Data Mining and Natural Language Processing co-located with The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2014), pages 49--63, CEUR Workshop Proceedings, 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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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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Eneldo Loza Mencía and Frederik Janssen, Stacking Label Features for Learning Multilabel Rules, in: Discovery Science - 17th International Conference, DS 2014, Bled, Slovenia, October 8-10, 2014, Proceedings, pages 192-203, Springer, 2014
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Axel Schulz and Frederik Janssen, What Is Good for One City May Not Be Good for Another One: Evaluating Generalization for Tweet Classification Based on Semantic Abstraction, in: Proceedings of the Fifth Workshop on Semantics for Smarter Cities (a Workshop at the 13th International Semantic Web Conference (ISWC 2014)), Riva del Garda, Italy, pages 53--67, 2014
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2013
Eneldo Loza Mencía and Frederik Janssen, Towards Multilabel Rule Learning, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2013, pages 155--158, 2013
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Eneldo Loza Mencía, Simon Holthausen, Axel Schulz and Frederik Janssen, Using Data Mining on Linked Open Data for Analyzing E-Procurement Information, in: Proceedings of the first DMoLD: Data Mining on Linked Data Workshop at ECML/PKDD2013, 2013
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2012
Frederik Janssen, Heuristic Rule Learning, TU Darmstadt, Knowledge Engineering Group, 2012
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Frederik Janssen and Markus Zopf, The SeCo-Framework for Rule Learning, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2012, Dortmund, Germany, 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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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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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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2009
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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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
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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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
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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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
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
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2006
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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