James Reilly
Pearl Pu
Barry Smyth
ABSTRACT
Conversational recommender systems are designed to help users to more efficiently navigate complex product spaces by alternatively making recommendations and inviting users' feedback. Compound critiquing techniques provide an efficient way for users to feed back their preferences (in terms of several simultaneous product attributes) when interfacing with conversational recommender systems. For example, in the laptop domain a user might wish to express a preference for a laptop that is "Cheaper, Lighter, with a Larger Screen". While recently a number of techniques for dynamically generating compound critiques have been proposed, to date there has been a lack of direct comparison of these approaches in a real-user study. In this paper we will compare two alternative approaches to the dynamic generation of compound critiques based on ideas from data mining and multi-attribute utility theory. We will demonstrate how both approaches support users to more efficiently navigate complex product spaces highlighting, in particular, the influence of product complexity and interface strategy on recommendation performance and user satisfaction.
- R. Agrawal, H. Mannila, R. Srikant, H. Toivonen, and A. I. Verkamo. Fast discovery of association rules. In Advances in Knowledge Discovery and Data Mining, pages 307--328. AAAI/MIT Press, 1996. Google Scholar
Digital Library
- D. Aha, L. Breslow, and H. Munoz-Avila. Conversational case-based reasoning. Applied Intel ligence, 14:9--32, 2001. Google ScholarDigital Library
- R. Burke, K. Hammond, and B. Young. Knowledge-based navigation of complex information spaces. In Proceedings of the 13th National Conference on Artificial Intel ligence, pages 462--468. AAAI Press, 1996. Portland, OR. Google ScholarDigital Library
- R. Burke, K. Hammond, and B. Young. The findme approach to assisted browsing. IEEE Expert, 12(4):32--40, 1997. Google ScholarDigital Library
- A. Jameson, B. Großmann-Hutter, L. March, R. Rummer, T. Bohnenberger, and F. Wittig. When actions have consequences: Empirically based decision making for intelligent user interfaces. Knowledge-Based Systems, 14(1-2):75--92, 2001.Google ScholarDigital Library
- R. Keeney and H. Raiffa. Decisions with Multiple Objectives: Preferences and Value Tradeoffs. John Wiley and Sons, New York, 1976.Google Scholar
- K. McCarthy, L. McGinty, B. Smyth, and J. Reilly. On the evaluation of dynamic critiquing: A large-scale user study. In Proceedings of the Twentieth National Conference on Artificial Intel ligence and the 17th Innovative Applications of Artificial Intel ligence Conference (AAAI-2005), pages 535--540. AAAI Press AAAI Press / The MIT Press, 2005. July 9-13, 2005, Pittsburgh, Pennsylvania, USA. Google ScholarDigital Library
- K. McCarthy, J. Reilly, L. McGinty, and B. Smyth. Experiments in dynamic critiquing. In Proceedings of the 10th International Conference on Intel ligent User Interfaces (IUI '05), pages 175--182. ACM Press, 2005. San Diego, CA, USA. Google ScholarDigital Library
- K. McCarthy, J. Reilly, L. McGinty, and B. Smyth.Generating diverse compound critiques. Artifical Intel ligence Review, 24:339--357, 2005. Google ScholarDigital Library
- L. McGinty and B. Smyth. Evaluating preference-based feedback in recommender systems. In Proceedings of the 13th Irish International Conference on Artificial Intel ligence and Cognitive Science (AICS-2002), pages 209--214. Springer, 2002. Limerick, Ireland. Google ScholarDigital Library
- L. McGinty and B. Smyth. Tweaking critiquing. In Proceedings of the Workshop on Intel ligent Techniques for Personalization as part of The 18th International Joint Conference on Artificial Intel ligence, (IJCAI-03), pages 20--27, 2003. Acapulco, Mexico.Google Scholar
- D. McSherry. Similarity and compromise. In Proceedings of the 5th International Conference on Case-Based Reasoning (ICCBR 2003), pages 291--305. Springer, 2003. Trondheim, Norway, June 23-26, 2003. Google ScholarDigital Library
- P. Pu and L. Chen. Integrating tradeoff support in product search tools for e-commerce sits. In Proceedings of the ACM Conference on Electronic Commerce (EC'05), pages 269--278, Vancouver, Canada, 2005. Google ScholarDigital Library
- P. Pu and P. Kumar. Evaluating example-based search tools. In Proceedings of the ACM Conference on Electronic Commerce (EC'04), pages 208--217, New York, USA, 2004. Google ScholarDigital Library
- J. Reilly, K. McCarthy, L. McGinty, and B. Smyth. Dynamic critiquing. In Proceedings of the 7th European Conference on Case-Based Reasoning (ECCBR-04), pages 763--777. Springer, 2004. Madrid, Spain.Google ScholarCross Ref
- J. Reilly, K. McCarthy, L. McGinty, and B. Smyth. Incremental critiquing. In Research and Development in Intel ligent Systems XXI. Proceedings of AI-2004, pages 101--114. Springer, 2004. Cambridge, UK.Google Scholar
- J. Reilly, J. Zhang, L. McGinty, P. Pu, and B. Smyth. A comparison of two compound critiquing systems. In Proceedings of the 12th International Conference on Intel ligent User Interfaces (IUI '07). ACM Press, 2007. Google ScholarDigital Library
- P. Resnick, N. Iacovou, M. Suchak, P. Bergstorm, and J. Riedl. Grouplens: An open architecture for collaborative filtering of netnews. In Proceedings of ACM 1994 Conference on Computer Supported Cooperative Work, pages 175--186, Chapel Hill, North Carolina, 1994. ACM. Google ScholarDigital Library
- J. B. Schafer, J. Konstan, and J. Riedl. E-commerce recommendation applications. Data Mining and Knowledge Discovery, 5(1/2):115--153, 2001. Google ScholarDigital Library
- J. Zhang and P. Pu. A comparative study of compound critique generation in conversational recommender systems. In Proceedings of the 4th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems (AH 2006), pages 234--243. Springer, 2006. Dublin, Ireland, June 21-23, 2006. Google ScholarDigital Library
Index Terms
- Evaluating compound critiquing recommenders: a real-user study
Recommendations
A comparison of two compound critiquing systems
IUI '07: Proceedings of the 12th international conference on Intelligent user interfacesCompound critiques allow users to simultaneously express directional preferences over several product attributes. Presenting the user with compound critiques is not a new idea. The original Find-Me Systems (e.g., Car Navigator) showed static compound ...
A visual interface for critiquing-based recommender systems
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