What is CBR 2.0?

Web 2.0 is changing the way people learn and work. It is conceivable that the Web 2.0 trend will also have an impact on the use of web-based CBR and research into CBR systems. Based on the concept of Web 2.0, we have created the concept of case-based reasoning 2.0 (CBR 2.0). Not only has there been a change in the way that CBR systems are delivered, but the adoption of Web 2.0 technologies may further influence the roles that users play in case retrieval, reuse, revision and retention. Furthermore, most existing CBR systems only focus on the retrieval process in CBR and bypass the adaptation task entirely (Leake, Kinley, & Wilson, 1995). However, as the retrieved case is often not the same with the practical problem, it is necessary for CBR systems to have case adaptation support (Voss, 1996; Chang et al., 2004). Thus, similar to Web 2.0, we propose that CBR 2.0 describes a second generation of CBR systems, facilitated by the Web platform and involving a virtual user community and case adaptation support.

The purposes of integrating Web 2.0 with CBR include, but not limited to:
(1) forming a virtual user community to facilitate and encourage a culture of participation and collaboration in cases, drawing upon the perspectives and contributions of the user community;

(2) encouraging and enabling a community of users to share their own views on cases they have used, which will help to improve the quality of the case-base;

(3) encouraging and enabling users to share their knowledge, experience and lessons on the adaptation of cases to provide solutions in problem solving (specifically, under circumstances when adaptation is needed, determining how the retrieved solution(s) can be adapted to reflect differences between the new case as solved by the user and the original retrieved case(s)); and

(4) encouraging and enabling users to share their experiences in case retrieval, case revision, case reuse, and case retention.

Any suggestions or feedback about this topic is welcome!

References

Leake, D.B., Kinley, A., & Wilson, D. (1995). Learning to improve case adaptation by introspective reasoning and CBR. Case-Based Reasoning Research and Development, Veloso, M., & Aamodt, A. (Eds.), Lecture Notes in Artificial Intelligence 1010, Springer-Verlag, Berlin.

Voss, A.(1996). How to solve complex problems with case. Engineering Applications of Artificial Intelligence, Vol 9, N0.4, pp.377-384,1996.

Chang, C.G., Cui, J.J., Wang, D.W., & Hu, K.Y. (2004). Research on case adaptation techniques in case-based reasoning. Proceedings of the Third International Conference on Machine Leaning and Cybernetics, Vol 4, pp.2128-2133, Shanghai, China, 2004.