Abstract
E-commerce sites can have large, essentiallyunbounded, catalogs. With large catalogs comesincreasing difficulty for buyers in making useof standard search and browsing facilities.Particularly in the case of casual oroccasional buyers and in the case of complexproducts, the gap between a product'sspecifications and the buyer's understanding ofneed can be hard to bridge. An effectivee-commerce catalog must map user needs toproducts that can fulfill them. This paperdescribes an interactive, incremental,case-based, critiquing approach to solving thisproblem. The approach is interactive andincremental, so it does not require that theuser have a completely specified need at thestart. The system is case-based in that itemphasizes products over features orconstraints, and uses case-based reasoningtechniques for its product retrieval. Finally,the approach is based on the critiquing ofpresented examples, each critique redirectingthe search to home in on appropriate products.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Bergmann, R., Breen, S., Göker, M., Manago, M. & Wess, S. (1999). Developing Industrial Case-Based Reasoning Applications: The INRECA Methodology. Lecture Notes in Artificial Intelligence, LNAI 1612. Berlin: Springer-Verlag
Burke, R. (1999). The Wasabi Personal Shopper: A Case-Based Recommender System. In Proceedings the 11th Annual Conference on Innovative Applications of Artificial Intelligence. Menlo Park, CA: AAAI Press.
Burke, R. (2000). Knowledge-Based Recommender Systems. In Kent, A. (ed.) Encyclopedia of Library and Information Systems, 69, Supplement 32.
Burke, R. (in press). Hybrid Recommender Systems: Survey and Experiments. User Modeling and User Adapted Interaction.
Burke, R., Hammond, K. & Young, B. (1997). The FindMe Approach to Assisted Browsing. IEEE Expert 12: 32–40.
Cutting, D. R., Pederson, J. O., Charger, D. & Turkey, J. W. (1992). Scatter/Gather: A cluster-based approach to browsing large document collections. In Proceedings of the 15th Annual International ACM/SIGIR Conference, 318–329. New York: ACM Press.
Ferguson, A. & Bridge, D. (2000). Partial Orders and Indifference Relations: Being Purpose-fully Vague in Case-Based Retrieval. In Blanzieri, E. & Portinale, L. (eds.) Advances in Case-Based Reasoning (EWCBR-00), Lecture Notes in AI 1898, 74–85. Berlin: Springer-Verlag.
Ferguson, W., Bareiss, R., Birnbaum, L. & Osgood, R. (1992). ASK Systems: An Approach to the Realization of Story-Based Teachers. Journal of the Learning Sciences 2, 95–134.
Foskett, D. J. (1980). Thesaurus. In Kent, A., Lancour, H. & Daily, J. E. (eds.) Encyclopedia of Library and Information Science 30, 416–462. New York: Marcel Dekker. Reprinted in K. Sparck-Jones and P. Willett (eds.) Readings in Information Retrieva, 111–134. San Francisco: Morgan Kaufmann.
Goldberg, D., Nichols, D., Oki, B. M. & Terry, D. (1992). Using Collaborative Filtering to Weave an Information Tapestry. Communications of the ACM 35, 61–70.
Guttman, R. H. (1998). Merchant Differentiation through Integrative Negotiation in Agent-mediated Electronic Commerce. Master's Thesis, School of Architecture and Planning, Program in Media Arts and Sciences, Massachusetts Institute of Technology.
Hagen, P. R., Manning, H. & Paul, Y. (2000). Must Search Stink? The Forrester Report (June). Hill, W.C., Stead, L., Rosenstein, M. and Furnas, G. (1995). Recommending and Evaluating Choices in a Virtual Community of Use. In Proceedings of TICHI'95, 194–201. Denver CO: ACM Press, May
Keeney, R. L. & Raiffa, H. (1993). Decisions with Multiple Objectives. Cambridge, UK: Cambridge University Press.
Kolodner, J. (1993). Case-Based Reasoning. San Mateo, CA: Morgan Kaufmann.
Konstan, J., Miller, B., Maltz, D., Herlocker, J., Gordon, L. & Riedl, J. (1997). GroupLens: Applying Collaborative Filtering to Usenet News. Communications of the ACM 40, 77–87.
Maes, P., Guttman, R. H. & Moukas, A. G. (1999). Agents that Buy and Sell. Communications of the ACM 42, 81–91.
Mullen, B. & Johnson, C. (1990). The Psychology of Consumer Behavior. Hillsdale, N.J.: Lawrence Erlbaum Assoc.
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P. & Riedl, J. (1994). GroupLens: An Open Architecture for Collaborative Filtering of Netnews. In CSCW' 94: Proceedings of the Conference on Computer Supported Cooperative Work, 175–186. New York: ACM Press.
Riesbeck, C. & Schank, R. C. (1989). Inside Case-Based Reasoning. Hillsdale, NJ: Lawrence Erlbaum.
Salton, G. & McGill, M. (1983). Introduction to Modern Information Retrieval.NewYork: McGraw-Hill.
Schafer, J. B., Konstan, J. & Riedl, J. (1999). Recommender Systems in E-Commerce. In EC' 99: Proceedings of the First ACM Conference on Electronic Commerce, 158–166. Denver, CO.
Schank, R. C. & Riesbeck, C. (1981). Inside Computer Understanding: Five Programs with Miniatures. Hillsdale, New Jersey: Lawrence Erlbaum Associates.
Schneiderman, B. (1994). Dynamic Queries for Visual Information Seeking. IEEE Software 11, 70–77.
Shardanand, U. & Maes, P. (1995). Social Information Filtering Algorithms for Automating “Word of Mouth” In CHI-95: Conference Proceedings on Human Factors in Computing Systems, 210–217. New York: ACM Press.
Smyth, B. & McClave, P. (2001). Similarity vs. Diversity. In Aha, D. W. & Watson, I. (eds.) Case-Based Reasoning Research and Development (ICCBR-01), Lecture Notes in AI 2080, 347–361. Berlin: Springer-Verlag
Vollrath, I., Wilke, W. & Bergmann, R. (1998). Case-Based Reasoning Support for Online Catalog Sales. IEEE Internet Computing 2: 47–54.
Watson, I. (1997). Applying Case-Based Reasoning: Techniques for Enterprise Systems San Francisco: Morgan Kaufmann.
Rights and permissions
About this article
Cite this article
Burke, R. Interactive Critiquing forCatalog Navigation in E-Commerce. Artificial Intelligence Review 18, 245–267 (2002). https://doi.org/10.1023/A:1020701617138
Issue Date:
DOI: https://doi.org/10.1023/A:1020701617138