Tutorials

• CBR Frameworks
• iSee - Explanation Experiences reuse with CBR

CBR Frameworks

In the last three decades of ICCBR, several CBR frameworks have been developed in several research groups. However, it is not easy, especially for young researchers, to know which CBR frameworks are being actively developed and what features they provide for their research. For this purpose, the ICCBR community will highly benefit from a tutorial in which the most prominent CBR frameworks will be presented in a short time and an overview of the framework features will be given. We, researchers and developers from four different universities, intend to give a tutorial for the CBR frameworks developed at our departments.

The CBR frameworks introduced in this tutorial are:

• CloodCBR - Microservices-oriented CBR Framework
• eXiT*CBR - A framework for case-based medical diagnosis development and experimentation(follow the link to download the tutorial material)
• myCBR - Similarity-based retrieval tool and Software Development Kit
• ProCAKE - Process-Oriented Case-Based Knowledge Engine (click here to access the tutorial material)

Organizers: Beatriz López (University of Girona, ES), Lukas Malburg (Univerity of Trier/DFKI, DE), Ikechukwu Nkisi-Orji (Robert Gordon University, GB), Chamath Palihawadana (Robert Gordon University, GB), Pascal Reuss (University of Hildesheim, DE), Jakob Schönborn (University of Hildesheim, DE), Alexander Schultheis (DFKI, DE)

iSee - Explanation Experiences reuse with CBR

iSee is a CHIST-ERA funded project being developed by a consortium of European universities (Complutense University of Madrid, Robert Gordon University, University College Cork) and an industrial partner (BT France). iSee is an XAI platform that captures, stores and re-uses end-user explanation experiences using the Case-based Reasoning methodology.

Cases are formed of knowledge of the AI model and its user group (problem component), the explanation strategy recommended (solution component), and feedback from the user group to describe whether the provisioned explanations were satisfactory (outcome component). In this manner, cases represent a comprehensive record of explanation experience. In this tutorial, the iSee project team would like to share with the participants the latest developments of this project, especially:

• How explanation experiences are represented in an ontology created for the project
• How explanations experiences are captured in a case-based database
• How use cases can be designed and represented in the system
• How explanations are progressively and interactively provided to end-users using conversation and how they can be evaluated.
• How end-user evaluations are measured and used to retain the explanations strategies in the case base.

The tutorial will culminate in attendees being able to add a mock case to the system, and receive recommendations of an explanation strategy to suit that case. Pending interest from the academic community, the tutorial may be expanded to include an interactive component demonstrating the uploading of XAI algorithms to iSee explainer API for broader industry impact.

Organizers: Anne Liret (British Telecommunications, FR), Bruno Fleisch ( British Telecommunications, FR), Chamath Palihawadana (Robert Gordon University, GB)