Keywords:
Publications of Frederik Janssen sorted by journal and type
Machine Learning
| and , Learning rules for multi-label classification: a stacking and a separate-and-conquer approach (2016), in: Machine Learning, 105:1(77--126) |
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| and , On the Quest for Optimal Rule Learning Heuristics (2010), in: Machine Learning, 78:3(343--379) |
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Semantic Web Journal
| , and , Semantic Abstraction for Generalization of Tweet Classification: An Evaluation on Incident-Related Tweets (2017), in: Semantic Web Journal, 8:3(353--372) |
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2016
| Big Data Analytics in the Social and Ubiquitous Context, Springer, Lecture Notes in Computer Science, volume 9546, 2016 |
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2015
| , , , and , 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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2014
| and , 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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2017
| , and , 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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2016
| , and , 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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| , and , 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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| , and , 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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| , , , , and , 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
| , , and , 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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| , , and , 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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| , , and , 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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| , and , 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
| , and , 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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| , , and , 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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| , and , 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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| and , 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
| and , Towards Multilabel Rule Learning, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2013, pages 155--158, 2013 |
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| , , and , 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
| , , , , , , and , HotMatch results for OEAI 2012, in: Seventh International Workshop on Ontology Matching (OM 2012), 2012 |
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| and , The SeCo-Framework for Rule Learning, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2012, Dortmund, Germany, 2012 |
| , , and , 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
| and , 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
| and , 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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2009
| and , 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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| , , and , 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 |
| , and , 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
| and , 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 |
| and , 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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2007
| and , 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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| and , Meta-Learning Rule Learning Heuristics, in: Proceedings of the German Workshop on Lernen, Wissen, Adaptivität - LWA2007, pages 167--174, 2007 |
| and , 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
| and , 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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| , Eine Untersuchung des Trade-Offs zwischen Precision and Coverage bei Regel-Lern-Heuristiken, TU Darmstadt, Knowledge Engineering Group, 2006 |
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2013
| , , and , Creating Noise Pollution Maps Based on User-generated Noise Data, Online, AI Mashup Challenge 2013 at ESWC, 2013 |
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2012
| , Heuristic Rule Learning, TU Darmstadt, Knowledge Engineering Group, 2012 |
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2009
2015
| , and , Advances in Predictive Maintenance for a Railway Scenario - Project Techlok, Knowledge Engineering Group, 2015 |
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| , and , 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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2014
| , and , Data-driven Detection of Congestion-affected Roads, Knowledge Engineering Group, Technische Universität Darmstadt, number TUD–KE–2014–02, 2014 |
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2010
| and , Separate-and-conquer Regression, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-01, 2010 |
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| and , The SeCo-framework for rule learning, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2010-02, 2010 |
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2008
| and , 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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| and , An Empirical Quest for Optimal Rule Learning Heuristics, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2008-01, 2008 |
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2007
| and , Meta-Learning Rule Learning Heuristics, TU Darmstadt, Knowledge Engineering Group, number TUD-KE-2007-02, 2007 |
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