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ORCIDFrederik Janssen
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2010 – 2019
- 2017
[j4]Axel Schulz, Christian Guckelsberger
, Frederik Janssen:
Semantic Abstraction for generalization of tweet classification: An evaluation of incident-related tweets. Semantic Web 8(3): 353-372 (2017)- [c28]Andrei Tolstikov, Frederik Janssen, Johannes Fürnkranz:
Evaluation of Different Heuristics for Accommodating Asymmetric Loss Functions in Regression. DS 2017: 67-81 - [c27]Christian Meurisch, Artur Gogel, Benedikt Schmidt, Timo Nolle, Frederik Janssen, Immanuel Schweizer, Max Mühlhäuser:
Capturing Daily Student Life by Recognizing Complex Activities Using Smartphones. MobiQuitous 2017: 156-165 - 2016
- [j3]Eneldo Loza Mencía, Frederik Janssen:
Learning rules for multi-label classification: a stacking and a separate-and-conquer approach. Mach. Learn. 105(1): 77-126 (2016) - [c26]Sebastian Kauschke, Johannes Fürnkranz, Frederik Janssen:
Predicting Cargo Train Failures: A Machine Learning Approach for a Lightweight Prototype. DS 2016: 151-166 - [c25]Julius Stecher, Frederik Janssen, Johannes Fürnkranz:
Shorter Rules Are Better, Aren't They? DS 2016: 279-294 - [c24]Jan Ruben Zilke, Eneldo Loza Mencía, Frederik Janssen:
DeepRED - Rule Extraction from Deep Neural Networks. DS 2016: 457-473 - [c23]Christian Meurisch, Usman Naeem, Muhammad Awais Azam, Frederik Janssen, Benedikt Schmidt, Max Mühlhäuser:
Smarticipation: intelligent personal guidance of human behavior utilizing anticipatory models. UbiComp Adjunct 2016: 1227-1230 - [e2]Martin Atzmueller, Alvin Chin, Frederik Janssen, Immanuel Schweizer, Christoph Trattner:
Big Data Analytics in the Social and Ubiquitous Context - 5th International Workshop on Modeling Social Media, MSM 2014, 5th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2014, and First International Workshop on Machine Learning for Urban Sensor Data, SenseML 2014, Revised Selected Papers. Lecture Notes in Computer Science 9546, Springer 2016, ISBN 978-3-319-29008-9 [contents] - 2015
- [c22]Axel Schulz, Petar Ristoski, Johannes Fürnkranz, Frederik Janssen:
Event-based Clustering for Reducing Labeling Costs of Incident-Related Microposts. MUD@ICML 2015: 44-52 - [c21]Axel Schulz, Frederik Janssen, Petar Ristoski, Johannes Fürnkranz:
Event-Based Clustering for Reducing Labeling Costs of Event-related Microposts. ICWSM 2015: 686-689 - [c20]Axel Schulz, Jakob Karolus, Frederik Janssen, Immanuel Schweizer:
Accurate pollutant modeling and mapping: Applying machine learning to participatory sensing and urban topology data. NetSys 2015: 1-8 - [c19]Sebastian Kauschke, Frederik Janssen, Immanuel Schweizer:
On the Challenges of Real World Data in Predictive Maintenance Scenarios: A Railway Application. LWA 2015: 121-132 - 2014
- [c18]Eneldo Loza Mencía, Frederik Janssen:
Stacking Label Features for Learning Multilabel Rules. Discovery Science 2014: 192-203 - [c17]Sebastian Kauschke, Immanuel Schweizer, Michael Fiebrig, Frederik Janssen:
Learning to Predict Component Failures in Trains. LWA 2014: 71-82 - [c16]Alexander Gabriel, Heiko Paulheim, Frederik Janssen:
Learning Semantically Coherent Rules. DMNLP@PKDD/ECML 2014: 49-63 - [c15]Julius Stecher, Frederik Janssen, Johannes Fürnkranz:
Separating Rule Refinement and Rule Selection Heuristics in Inductive Rule Learning. ECML/PKDD (3) 2014: 114-129 - [c14]Axel Schulz, Frederik Janssen:
What Is Good for One City May Not Be Good for Another One: Evaluating Generalization for Tweet Classification Based on Semantic Abstraction. S4SC@ISWC 2014: 53-67 - 2013
- [c13]Eneldo Loza Mencía, Simon Holthausen, Axel Schulz, Frederik Janssen:
Using Data Mining on Linked Open Data for Analyzing E-Procurement Information - A Machine Learning approach to the Linked Data Mining Challenge 2013. DMoLD 2013 - [c12]Eneldo Loza Mencía, Frederik Janssen:
Towards Multilabel Rule Learning. LWA 2013: 144-147 - 2012
- [b1]Frederik Janssen:
Heuristic rule learning. Darmstadt University of Technology, Germany, 2012, pp. 1-217 - [c11]Frederik Janssen, Faraz Fallahi, Jan Noessner, Heiko Paulheim:
Towards Rule Learning Approaches to Instance-based Ontology Matching. KNOW@LOD 2012: 13-18 - [c10]Thanh-Tung Dang, Alexander Gabriel, Sven Hertling, Philipp Roskosch, Marcel Wlotzka, Jan Ruben Zilke, Frederik Janssen, Heiko Paulheim:
HotMatch results for OEAI 2012. OM 2012 - 2011
- [c9]Frederik Janssen, Johannes Fürnkranz:
Heuristic Rule-Based Regression via Dynamic Reduction to Classification. IJCAI 2011: 1330-1335 - [c8]Frederik Janssen, Johannes Fürnkranz:
Heuristic Rule-Based Regression via Dynamic Reduction to Classification. LWA 2011: 48-53 - 2010
- [j2]Frederik Janssen, Johannes Fürnkranz:
On the quest for optimal rule learning heuristics. Mach. Learn. 78(3): 343-379 (2010) - [c7]Frederik Janssen, Johannes Fürnkranz:
Separate-and-conquer Regression. LWA 2010: 81-88
2000 – 2009
- 2009
- [j1]Frederik Janssen, Melanie Hartmann:
LWA 2009. Künstliche Intell. 23(2): 72 (2009) - [c6]Frederik Janssen, Johannes Fürnkranz:
A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. SDM 2009: 329-340 - [e1]Melanie Hartmann, Frederik Janssen:
LWA 2009: Workshop-Woche: Lernen, Wissen, Adaptivität, Darmstadt, 21.-23. September 2009. FG Telekooperation/FG Knowledge Engineering, Technische Universität Darmstadt, Germany 2009 [contents] - 2008
- [c5]Frederik Janssen, Johannes Fürnkranz:
An Empirical Investigation of the Trade-Off between Consistency and Coverage in Rule Learning Heuristics. Discovery Science 2008: 40-51 - [c4]Frederik Janssen, Johannes Fürnkranz:
A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. LWA 2008: 42-49 - 2007
- [c3]Frederik Janssen, Johannes Fürnkranz:
On Meta-Learning Rule Learning Heuristics. ICDM 2007: 529-534 - [c2]Frederik Janssen, Johannes Fürnkranz:
Meta-Learning Rule Learning Heuristics. LWA 2007: 167-174 - 2006
- [c1]Frederik Janssen, Johannes Fürnkranz:
On Trading Off Consistency and Coverage in Inductive Rule Learning. LWA 2006: 306-313
Coauthor Index
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