Logo XCBR: Second Workshop on Case-based Reasoning for the explanation of intelligent systems

XCBR: Second Workshop on Case-based Reasoning for the explanation of intelligent systems

27th International Conference on Case-Based Reasoning September 8 – 12, 2019, in Otzenhausen, Germany

Call for Papers

Second Workshop on XCBR: Case-based Reasoning for the explanation of intelligent systems.

XCBR is a workshop aiming to provide a medium of exchange for information about trends, research issues and practical experiences in the use of Case-based Reasoning (CBR) methods for the inclusion of explanations to several AI techniques using reasoning-by-example.

The success of the intelligent systems has led to an explosion of the generation of new autonomous systems with new capabilities like perception, reasoning, decision support and self-actioning. Despite the tremendous benefits of these systems, they work as black-box systems and their effectiveness is limited by their inability to explain their decisions and actions to human users. The problem of explainability in Artificial Intelligence is not new but the rise of the autonomous intelligent systems has created the necessity to understand how these intelligent systems achieve a solution, make a prediction or a recommendation or reason to support a decision in order to increase users reliability in these systems. Additionally, the European Union included in their regulation about the protection of natural persons with regard to the processing of personal data a new directive about the need of explanations to ensure fair and transparent processing in automated decision-making systems.

The goal of Explainable Artificial Intelligence (XAI) is “to create a suite of new or modified machine learning techniques that produce explainable models that, when combined with effective explanation techniques, enable end users to understand, appropriately trust, and effectively manage the emerging generation of Artificial Intelligence (AI) systems”.

For this purpose, the XCBR workshop is intended to have a structure of activities that helps exchange of ideas and interaction, suited to highlight the main bottlenecks and challenges, as well as the more promising research lines, for CBR research related to the explanation of intelligent systems.

CBR systems have previous experiences in interactive explanations and in exploiting memory-based techniques to generate these explanations that can be successfully applied to the explanation of emerging AI and machine learning techniques.

Research contributions submitted to the workshop will be related to areas that include, but are not limited to, the following:

  • Generic explanation methods based on CBR for AI techniques.
  • Novel techniques for the visualization of case-based explanations.
  • Case-based explanation of deep-learning techniques.
  • Case-based explanation of big data techniques.
  • Case-based explanation of the massive data obtained from sensor systems, Internet of Things, or wearables.
  • Combination of existing AI models and CBR to provide explanation capabilities.
  • Application of Case-based explanation capabilities to different domains.
  • Lessons learned in XCBR investigations.
  • Challenge tasks for XCBR systems in novel AI techniques.


This workshop will be held on September 9th, 2019 as part of the ICCBR 2019 workshop series in Otzenhausen, Germany. This workshop is open to all interested conference participants but may be limited by available room facilities.

The Organizing Committee will select a subset of the submitted papers for oral presentation. In particular, we invite submissions both of short position papers (4 pages) and longer papers on research results (10 pages). Moreover, time will be reserved for ample discussion.

Workshop Schedule

The XCBR workshop will be held on September 9 with the following schedule:

9:00 Welcome
9:15 Joint Workshop Session: Invited Talk XCBR
David Aha: What's Happening in XAI Today? Summary of Recent Work and Status of the DARPA XAI Program
10:00 Coffe break
10:30 Jakob Michael Schoenborn and Klaus-Dieter Althoff Recent Trends in XAI: A Broad Overview on Current Approaches, Methodologies and Interactions
10:45 Panel: General Discussion, Trends and Future Plans for XCBR
11:15 Marta Caro-Martinez, Guillermo Jimenez-Diaz, and Juan A. Recio-Garcia A Survey of Techniques for the Evaluation of Explanations in Recommender Systems
11:30 Juan A. Recio-Garcia and Guillermo Jimenez-Diaz A Novel Interface for the Explanation of Group Recommendations using Augmented Reality
11:45 Juan A. Recio-Garcia, Belen Diaz-Agudo, Jose Jorro-Aragoneses and Marta Caro-Martinez SAFEWAY: An Explainable Context-Aware Recommender System for Safe Routes

Important Dates

July 3, 2019
Extended: July 12, 2019
Paper submission deadline
July 23, 2019 Notification of acceptance
August 9, 2019 Camera-ready submission
September 9, 2019 Workshop date

Program commitee

  • David Leake, Indiana University, USA
  • Derek Bridge, University College Cork, Ireland
  • Amélie Cordier, University Claude Bernard Lyon 1, France
  • Pedro A. González Calero, UCM, Madrid
  • Stelios Kapetanakis, University of Brighton, UK
  • Hector Muñoz‐Ávila, Lehigh University, USA
  • Santiago Ontañón, Drexel University, USA
  • Miltos Petridis, Middlesex University, UK
  • Enric Plaza, IIIA, CSIC, Spain
  • Lara Quijano, University Carlos III of Madrid, Spain
  • Ashwin Ram, Georgia Institute of Technology, USA
  • Antonio A. Sánchez Ruiz‐Granados, UCM, Spain
  • Barry Smyth, University College Dublin, Ireland
  • Ian Watson, University of Auckland, New Zealand
  • Nirmalie Wiratunga, Robert Gordon University, UK


Belén Díaz Agudo
Belén Díaz Agudo
University Complutense of Madrid, Spain
Juan A. Recio García
Juan A. Recio García
University Complutense of Madrid, Spain
Ian Watson
Ian Watson
University of Auckland, New Zealand