Abstract
We introduce an application combining CBR and collaborative filtering techniques in the music domain. We describe a scenario in which a new kind of recommendation is required, which is capable of summarizing many recommendations in one suggestion. Our claim is that recommending one set of goods is different from recommending a single good many times. The paper illustrates how a case-based reasoning approach can provide an effective solution to this problem reducing the drawbacks related to the user profiles. CoCoA, a compilation compiler advisor, will be described as a running example of a collaborative case-based recommendation system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
M. Berry and S. Dumais. Using linear algebra for intelligent information retrieval. SIAM Review 37(4), pages 573–595, 1995.
D. Billsus and M. J. Pazzani. Learning collaborative information filters. Technical report, AAAI, July 1998.
Padraig Cunningham, Ralph Bergmann, S. Schmitt, R. Traphoener, and S. Breen. Websell: Intelligent sales assistants for the world wide web. Technical report, Trinity College Dublin, 2000.
S. Deerwester, S.T. Dumais, G.W. Furnas, T.K. Landauer, and R. Harshman. Indexing by latent semantic analysis. Journal of the American Society for Information Science, pages 391–407, 1990.
George E. Forsythe, Michael A. Malcolm, and Cleve B. Moler. Computer Methods for Mathematical Computations. Prentice-Hall, Englewood Cliffs, NJ 07632, USA, 1977.
D. Goldberg, D. Nichols, B.M. Oki, and D. Terry. Using collaborative filtering to weave an information tapestry. Communications of the ACM, 35(12):61–70, 1992.
Gene H. Golub and Charles F. Van Loan. Matrix Computations. The Johns Hopkins University Press and North Oxford Academic, Baltimore, MD, USA and Oxford, England, 1983.
C. Hayes and P. Cunningham. Smart radio: Building music radio on the fly. In Expert Systems 2000, Cambridge, UK, 2000.
Thomas Hofmann. Probabilistic latent semantic analysis. pages 177–196, 2001.
P. McJones. Eachmovie collaborative filtering data set, dec systems research center, 1997. http://research.compaq.com/SRC/eachmovie/.
P. Resnick and H.R. Varian. Recommender systems. Communications of the ACM, 40(3):56–58, 1997.
B. M. Sarwar, G. Karypis, J. A. Konstan, and J. Riedl. Application of dimensionality reduction in recommender system-a case study. In ACM WebKDD 2000 Web Mining for E-Commerce Workshop, 2000.
J.B. Schafer, J. Konstan, J., and Riedl. Recommender systems in e-commerce. In Proceeding of the ACM Conference on Electronic Commerce, Pittsburgh, PA, USA, November 1999.
S. Schmitt and R. Bergmann. Applying case-based reasoning technology for product selection and customization in electronic commerce environments. In 12th Bled Electronic Commerce Conference, 1999.
Armin Stahl and Ralph Bergmann. Applying recursive CBR for the customization of structured products in an electronic shop. In EWCBR, pages 297–308, 2000.
Wolfgang Wilke, Mario Lenz, and Stefan Wess. Intelligent sales support with CBR. In Case-Based Reasoning Technology, pages 91–114, 1998.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Aguzzoli, S., Avesani, P., Massa, P. (2002). Collaborative Case-Based Recommender Systems. In: Craw, S., Preece, A. (eds) Advances in Case-Based Reasoning. ECCBR 2002. Lecture Notes in Computer Science(), vol 2416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46119-1_34
Download citation
DOI: https://doi.org/10.1007/3-540-46119-1_34
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44109-0
Online ISBN: 978-3-540-46119-7
eBook Packages: Springer Book Archive