Foto: Staatliche Schlösser und Gärten Baden-Württemberg
Day 3: Friday 24.8
9:00-10:00: Keynote 4 (A001)
Stephan Mandt: Finding Hidden Structure in Data with Deep Probabilistic Models.
10:00-10:30: Coffee Break (Foyer EG)
10:30-12:00: Joint Session 2 (A001)
- Jakob Huber, Alexander Gossmann and Heiner Stuckenschmidt: Cluster-based Hierarchical Demand Forecasting for Perishable Goods
- Video: Joint Session 2
- Andreas Korger and Joachim Baumeister: The SECCO Ontology for the Retrieval and Generation of Security Concepts
- Video: Joint Session 2
- Ralph Bergmann, Ralf Schenkel, Lorik Dumani and Stefan Ollinger: ReCAP – Information Retrieval and Case-Based Reasoning for Robust Deliberation and Synthesis of Arguments in the Political Discourse
- Video: Joint Session 2
- Till Blume and Ansgar Scherp: Towards an Incremental Schema-level Index for Distributed Linked Open Data Graphs
- Video: Joint Session 2
12:00-13:30: Lunch (Mensa)
13:30-15:00: Parallel Sessions 3
FGIR (A103)
- Chanjong Im, Junaid Ghauri, John Rothman and Thomas Mandl: Deep Learning Approaches to Classification of Production Technology for 19th Century Books
- Andreas Henrich and Markus Wegmann: Search for an Appropriate Journal – in Depth Evaluation of Data Fusion Techniques
FGWM (A101)
- Joachim Baumeister: Evaluation of Configuration Knowledge in Industrial Manufacturing
- Lisa Grumbach, Eric Rietzke, Markus Schwinn, Ralph Bergmann and Norbert Kuhn: SEMANAS – Semantic Support for Grant Application Process
- Gerhard Peter: Design of Enterprise Social Media: Recommendations from a Case Study
- Andrea Kohlhase: Factors for Reading Mathematical Expressions
- Pascal Reuss, Sebastian Viefhaus and Klaus-Dieter Althoff: Case-based Action Planning in a First-Person Scenario
KDML (A104)
- Patrick Klein and Ralph Bergmann: Data Generation with a Physical Model to Support Machine Learning Research for Predictive Maintenance
- Hien Dang and Johannes Fürnkranz: Exploiting Maneuver Dependency for Personalization of a Driver Model
- Alexandru Ciobanu, Asmaa Haja and Andreas Lommatzsch: Normalization of Timeseries for Improving Recommendations
- Mirko Bunse, Nico Piatkowski and Katharina Morik: Towards a Unifying View on Deconvolution in Cherenkov Astronomy
- Tomas Kliegr and Vaclav Zeman: EasyMiner.eu: Web framework for interpretable machine learning based on rules and frequent itemsets