The development of appropriate technologies to enable direct and efficient access to relevant information is one of the key challenges for the information society. Traditional database query languages are optimized to reconcile large volume data stocks with great efficiency based on exactly specified queries. Today, many application scenarios demand more advanced technologies that offer intelligent support to the user when searching for information.
In the area of e-Commerce, for example, the user searching for a product is seldom in a position to formulate an appropriate, exact specification for a query. Frequently, either the necessary background knowledge about the product offering is lacking or, over or under specified database queries lead to empty or unmanageable results, which is of little help in finding a suitable available product. Intelligent product recommendation systems present an alternative which, even with relatively vague desires and needs on the part of the user, can recommend suitable, target oriented products.
Such knowledge based product recommendation systems are being developed primarily on the basis of technologies from the field of Case-Based Reasoning or CBR. The central idea here is to search on the basis of similarities to the stated inquiry, which always enables the return of the most appropriate, available information sorted by relevance. A major role is played by the inclusion of knowledge domains in the form of ontologies and other application specific similarity measures.

myCBR is an open-source case-based reasoning tool developed at DFKI.
Its aims are:

• to be easy to use,
• to enable fast prototyping,
• to be extendable and adaptable, and
• to integrate state-of-the-art CBR functionality.

Thus it supports the teaching and research of the CBR approach.

myCBR 2.x builds on top of Protégé, which already provides advanced functionality for defining and visualizing object-oriented case representations. The myCBR retrieval engine is provided as a standalone application as well.

News

• 10/08/30 Check out the new myCBR 3.0 BETA: myCBR 3.0 BETA

Current Features

• Powerful GUIs for modeling knowledge-intensive similarity measures
• Similarity-based retrieval functionality
• Export of domain model (including similarity measures) in XML
• Additional stand-alone retrieval engine
• Extension to structured object-oriented case representations, including helpful taxonomy editors
• Powerful textual similarity modelling which distinguishes between word-based and character-based measures; it even supports regular expressions
• Scriptable similarity measures using Jython
• Rapid prototyping via CSV

Features myCBR 3.0 BETA

• Improved scalability
• Simple data model (applications can easily be build on top)
• Fast retrieval results
• Rapid loading of large case bases

Collaboration

jCOLIBRI is a generic CBR framework in Java developed by Universidad Complutense de Madrid - GAIA research group. There is a contribution which provides wrapper methods to use similarity measures generated with myCBR 2.x within jCOLIBRI.
For more information, please visit gaia.fdi.ucm.es/projects/jcolibri/jcolibri2/contributions.html