Explanation Support for the Case-Based Reasoning Tool myCBR

Case-Based Reasoning, in short, is the process of solving new problems based on solutions of similar past problems, much like humans solve many problems. myCBR, an extension of the ontology editor Protégé, provides such similaritybased retrieval functionality. Moreover, the user is supported in modelling appropriate similarity measures by forward and backward explanations. Case-Based Reasoning Case-Based Reasoning (CBR), according to (Aamodt & Plaza 1994), basically follows this pattern: One formulates a problem as a query case and the repository of already experienced problem and solution pairs (the case base) will be ordered by similarity to the given query. The most similar cases are used to generate the solution for the posed problem. After a solution is retrieved, the new case (consisting of the new problem and the retrieved solution) is stored in the case base. This new experience can be used in the next retrieval. The CBR system learns. CBR systems’ knowledge can be divided in four knowledge containers (Richter 1995): • Vocabulary This knowledge container is the basis for the three other containers. It defines attributes and classes for query and case descriptions. In object-oriented CBR systems the vocabulary consists of numerical, symbolic, plain text, and instance type attributes. • Case Base This is the collection of previously experienced cases (traditional view) or products. • Similarity Measure The degree of similarity between a query and a case is defined by metrics. Local similarity measures define similarities for each attribute. Global similarity measures, e.g., weighted sum, minimum, or maximum, aggregate the local similarity measures into one similarity value on each class level. • Adaptation Rules This container provides knowledge for adapting the solution of a case to fit the query. This is often realised with rules. Adaptation rules are outside the scope of this work. We concentrate on the support of similarity measure modelling. Copyright c © 2007, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. The Open-Source Tool myCBR myCBR1 is an open-source plug-in for the open-source ontology editor Protégé2. It follows in the footsteps of the integrated, Smalltalk-based CBR shell CBR-Works (Schulz 1999) with its rich point-and-click user interface. We also implemented a basic export interface to exchange similarity measures with jColibri, a powerful Java-based CBR framework3, which allows more complex reasoning. In Protégé users define classes and attributes in an objectoriented way. Protégé also manages instances of these classes, which we interpret as cases. So vocabulary and case base knowledge containers are already handled by Protégé. Figure 1: Similarity measure editors of myCBR The myCBR plug-in adds several similarity measure editors, which can be applied to the classes and attributes of an ontology. Its retrieval engine finds similar cases for a specified query. Additionally, CSV files can be imported for which a simple similarity model is built automatically if none exists. A standalone retrieval engine allows for easy integration into other applications. Figure 1 shows a screenshot of some of the available editors. http://mycbr-project.net http://protege.stanford.edu/ http://gaia.fdi.ucm.es/projects/jcolibri/