1st Workshop on Beyond Attribute-Value Case Representation (BEAR)

The authors of all accepted papers have to give a presentation of their work in the workshop. As the workshop will be joined with the TMG workshop, the program is identical. In the following, you find the schedule for the BEAR/TMG workshop. Each accepted paper will have 15–20 minutes for presentation and 10 minutes for discussion. 

Please find more detailed information at:
https://recap.uni-trier.de/workshops/tmg-2023/. 

Florian Brand, Katharina Lott, Lukas Malburg, Maximilian Hoffmann and Ralph Bergmann: Using Deep Reinforcement Learning for the Adaptation of Semantic Workflows

Lukas Malburg, Alexander Schultheis and Ralph Bergmann: Modeling and Using Complex IoT Time Series Data in Case-Based Reasoning: From Application Scenarios to Implementations

Joseph Kendall-Morwick: Working with Ambiguous Case Representations