Day 3: Friday 24.8

9:00-10:00: Keynote 4 (A001)

Stephan Mandt: Finding Hidden Structure in Data with Deep Probabilistic Models.

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

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