List of Accepted Papers

All papers are part of the technical program of ICCBR 2019 and will be presented as oral or poster presentations.

Oral Presentation:

Title Authors
On the Generalization Capabilities of Sharp Minima in Case-Based Reasoning Thomas Gabel and Eicke Godehardt
CBR Confidence as a Basis for Confidence in Black Box Systems Lawrence Gates, Caleb Kisby and David Leake
Predicting Grass Growth for Sustainable Dairy Farming: A CBR System Using Bayesian Case-Exclusion and Post-Hoc, Personalized Explanation-by-Example (XAI) Eoin Kenny, Elodie Ruelle, Anne Geoghegan, Laurence Shalloo, Micheál O’leary, Michael O’donovan and Mark Keane
Learning Workflow Embeddings to Improve the Performance of Similarity-Based Retrieval for Process-Oriented Case-Based Reasoning Patrick Klein, Lukas Malburg and Ralph Bergmann
On Combining Case Adaptation Rules David Leake and Xiaomeng Ye
Semantic Textual Similarity Measures for Case-Based Retrieval of Argument Graphs Mirko Lenz, Stefan Ollinger, Premtim Sahitaj and Ralph Bergmann
Improving analogical extrapolation using case pair competence Jean Lieber, Emmanuel Nauer and Henri Prade
Personalized case-based explanation of matrix factorization recommendations Jose Luis Jorro-Aragoneses, Marta Caro-Martinez, Juan Antonio Recio-Garcia, Belen Diaz-Agudo and Guillermo Jimenez-Díaz
Scoring Performance on the Y-Balance Test Vivek Mahato, William Johnston and Padraig Cunningham
An Optimal Casebase Maintenance Method for Compositional Adaptation Applications
Ditty Mathew and Sutanu Chakraborti
Probabilistic Selection of Case-Based Explanations in an Underwater Mine Clearance Domain Venkatsampath Raja Gogineni, Sravya Kondrakunta, Danielle Brown, Matthew Molineaux and Michael Cox
Going Further with Cases: Using Case-Based Reasoning to Recommend Pacing Strategies for Ultra-Marathon Runners Barry Smyth and Cathal McConnell
A Tale of Two Communities: An Analysis of Three Decades of Case-Based Reasoning Research Barry Smyth
How Case-Based Reasoning Explains Neural Networks Mark T Keane and Eoin M Kenny
NOD-CC: A Hybrid CBR-CNN Architecture for Novel Object Discovery Jt Turner, Michael Floyd, Kalyan Gupta and Tim Oates

 

Poster Presentation:

Title Author
Comparing Similarity Learning with Taxonomies and One-Mode Projection in Context of the FEATURE-TAK Framework Oliver Berg, Pascal Reuss, Rotem Stram and Klaus-Dieter Althoff
An Algorithm Independent Case-Based Explanation Approach for Recommender Systems Using Interaction Graphs Marta Caro-Martínez, Juan A. Recio-Garcia and Guillermo Jimenez-Diaz
Explanation of Recommender Systems using Formal Concept Analyisis Belen Diaz-Agudo, Marta Caro, Juan Recio-Garcia, Jose Luis Jorro Aragoneses and Guillermo Jimenez-Diaz
FLEA-CBR: A Flexible Alternative to the Classic 4R Cycle of Case-Based Reasoning Viktor Eisenstadt, Christoph Langenhan and Klaus-Dieter Althoff
Lazy Learned Screening for Efficient Recruitment Erik Espenakk, Magnus Johan Knalstad and Anders Kofod-Petersen
A Data-Driven Approach for Determining Weights in Global Similarity Functions Amar Jaiswal and Kerstin Bach
An approach to case-based reasoning based on local enrichment of the case base Yves Lepage and Jean Lieber
Towards Finding Flow in Tetris Diana Lora, Antonio A. Sánchez-Ruiz and Pedro González Calero
Towards Human-like Bots using Online Interactive Case-Based Reasoning Maximiliano Miranda, Antonio A. Sánchez-Ruiz and Federico Peinado
Show me your friends, I’ll tell you who you are: Recommending products based on hidden evidence Anbarasu Sekar and Sutanu Chakraborti
Adaptation of Scientific Workflows by Means of Process-Oriented Case-Based Reasoning
Christian Zeyen, Lukas Malburg and Ralph Bergmann