ICCBR-WS 2023
ICCBR 2023 Workshop Proceedings

Table of Contents

• Preface and Table of Contents1
  Summary: There were 20 papers submitted for peer-reviews to the workshops. Out of these, 15 papers were accepted as regular papers for this volume.

ATA: Workshop on Analogies: from Theory to Applications - AR & CBR Tools for Metric and Representation Learning

• Preface2
  
• Resolution of Analogies Between Strings in the Case of Multiple Solutions 3-14
  Xulin Deng, Yves Lepage
• Embedding-To-Embedding Method Based on Autoencoder for Solving Sentence Analogies 15-26
  Weihao Mao, Yves Lepage
• Less is Better: An Energy-Based Approach to Case Base Competence 27-42
  Esteban Marquer, Fadi Badra, Marie-Jeanne Lesot, Miguel Couceiro, David Leake
• Improving Sentence Embedding With Sentence Relationships From Word Analogies 43-53
  Qixuan Zhang, Yves Lepage

BEAR: Workshop on Beyond Attribute-Value Case Representation

• Preface54
  
• Using Deep Reinforcement Learning for the Adaptation of Semantic Workflows 55-70
  Florian Brand, Katharina Lott, Lukas Malburg, Maximilian Hoffmann, Ralph Bergmann
• Working with Ambiguous Case Representations 71-80
  Joseph Kendall-Morwick
• Modeling and Using Complex IoT Time Series Data in Case-Based Reasoning: From Application Scenarios to Implementations 81-96
  Lukas Malburg, Alexander Schultheis, Ralph Bergmann

TMG: Workshop on Text Mining and Generation

• Preface97
  
• Knowledge Base Question Answering by Transformer-Based Graph Pattern Scoring 98-113
  Marcel Lamott, Jörn Hees, Adrian Ulges
• Trust me, I am an Expert: Predicting the Credibility of Experts for Statements 114-128
  Markus Nilles, Lorik Dumani, Björn Metzler, Ralf Schenkel
• Argument-Mining from Podcasts Using ChatGPT 129-144
  Mircea-Luchian Pojoni, Lorik Dumani, Ralf Schenkel

XCBR: Workshop on Case-Based Reasoning for the Explanation of Intelligent Systems

• Preface145
  
• A Twin XCBR System Using Supportive and Contrastive Explanations 146-157
  Betül Bayrak, Kerstin Bach
• Impact of Weight Functions on Preferred Abductive Explanations for Decision Trees 158-171
  Louenas Bounia, Matthieu Goliot, Anasse Chafik
• The Current and Future Role of Visual Question Answering in eXplainable Artificial Intelligence 172-183
  Marta Caro-Martínez, Anjana Wijekoon, Belén Díaz-Agudo, Juan A. Recio-García
• AGREE: A Feature Attribution Aggregation Framework to Address Explainer Disagreements with Alignment Metrics 184-199
  Craig Pirie, Nirmalie Wiratunga, Anjana Wijekoon, Carlos Francisco Moreno-Garcia
• Case-Based Explanation of Classification Models for the Detection of SQL Injection Attacks 200-215
  Juan A. Recio-García, Mauricio G. Orozco-del-Castillo, Jose A. Soladrero

Tutorial on CBR Frameworks

• Preface216-217
  

Tutorial on Explainable AI using CBR

• Preface218
  

ICCBR Doctoral Consortium 2023

• Preface and Table of Contents219-221
  
• Investigating the duality of CBR: Performance and Interpretability 222-227
  Prateek Goel
• Exploring Deep Learning-Based Feature Extraction for Case-Based Reasoning Retrieval 228-232
  Zachary Wilkerson
• Beyond Post-Hoc Instance-Based Explanation Methods 233-238
  Betül Bayrak
• Circularity in Case-Based Reasoning 239-244
  Adwait P. Parsodkar
• Feature Deletion and Case Discovery in Case-Base Maintenance 245-250
  Brian Schack