Abstract
When it comes to buying expensive goods people expect to be skillfully steered through the options by well-informed sales assistants who are capable of balancing the user’s many and varied requirements. In addition users often need to be educated about the product space, especially if they are to come to understand what is available and why certain options are being recommended by the sales-assistant. It is now well accepted that interactive recommender systems, the on-line equivalent of a sales assistant, also need to educate users about the product space and to justify their recommendations. In this paper we focus on a novel approach to explanation. Instead of attempting to justify a particular recommendation we focus on how certain types of feedback can help users to understand the recommendation opportunities that remain if the current recommendation should not meet their requirements. Specifically, we describe how this approach to explanation is tightly coupled with the generation of compound critiques, which act as a form of feedback for users. Furthermore, we argue that these explanation-rich critiques have the potential to dramatically improve recommender performance and usability.
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A. Aamodt (1994) Explanation-Driven Case-Based Reasoning S. Wess K. Althoff M. Richter (Eds) Proceedings of the European Workshop on Case-Based Reasoning (EWCBR-94) Springer Berlin Germany 274–288
R. Agrawal H. Mannila R. Srikant H. Toivonen A. I. Verkamo (1996) Fast Discovery of Association Rules in Large Databases. Advances in Knowledge Discovery and Data Mining AAAI Press Portland 307–328
Barletta, R. & Mark, W. (1988). Explanation-Based Indexing of Cases. In: Proceedings of the Seventh National Conference on Artificial Intelligence (AAAI-88), 541–546. AAAI. Minneapolis, MN, US.
Burke, R., Hammond, K. & Young, B. (1996). Knowledge-Based Navigation of Complex Information Spaces. In Proceedings of the Thirteenth National Conference on Artificial Intelligence, 462–468. AAAI Press/MIT Press: Portland, OR.
R. Burke K. Hammond B. Young (1997) ArticleTitleThe FindMe Approach to Assisted Browsing Journal of IEEE Expert 12 IssueID4 32–40 Occurrence Handle10.1109/64.608186
P. Cunningham D. Doyle J. Loughrey (2003) An Evaluation of the Usefulness of Case-Based Explanation K. Ashley D. Bridge (Eds) Case-Based Reasoning Research and Development. LNAI, Vol. 2689 Springer-Verlag Berlin, Heidelberg 122–130
D. Doyle P. Cunningham D. Bridge Y. Rahman (2004) Explanation Oriented Retrieval P.A. Gonzalez-Calero P. Funk (Eds) Advances in Case-Based Reasoning (ECCBR-04) Springer-Verlag Berlin, Heidelberg 157–168
Gervás, P. & Gupta, K.M. (eds.) 2004. Proceedings of the ECCBR 2004 Workshops. Technical Report 142–04, Departamento de Sistemas Informáticos y Programación, Universidad Complutense de Madrid: Madrid, Spain.
M. Gu A. Aamodt (2004) Explanation-Boosted Question Selection in Conversational CBR P. Gervás K.M. Gupta (Eds) Proceedings of the ECCBR 2004 Workshops Departamento de Sistemas Informáticos y Programación, Universidad Complutense de Madrid Madrid, Spain 105–114
Z. Hu W. Chin M. Takeichi (2000) Calculating a New Data Mining Algorithm for Market Basket Analysis Springer-Verlag Berlin 169–175
L. Ihrig S. Kambhampati (1995) An Explanation-Based Approach to Improve Retrieval in Case-Based Planning M. Ghallab A. Milani (Eds) Proceedings of the European Workshop on Planning (EWSP-95) IOS Press Amsterdam 395–406
K. McCarthy J. Reilly L. McGinty B. Smyth (2004) On the Dynamic Generation of Compound Critiques in Conversational Recommender Systems P.D. Bra (Eds) Proceedings of the Third International Conference on Adaptive Hypermedia and Web-Based Systems (AH-04) Springer-Verlag Eindhoven, The Netherlands 176–184
McGinty, L. & Smyth, B. (2003). Tweaking Critiquing. In: Proceedings of the Workshop on Personalization and Web Techniques at the International Joint Conference on Artificial Intelligence (IJCAI-03), 20–27. Morgan-Kaufmann: Acapulco, Mexico.
McSherry, D. (2003). Explanation in Case-Based Reasoning: An Evidential Approach. In: Lees, B. (ed.) Proceedings of the 8th UK Workshop on Case-Based Reasoning. Cambridge, UK.
D. McSherry (2004a) Explaining the Pros and Cons of Conclusions in CBR P. A. González-Calero P. Funk (Eds) Advances in Case-Based Reasoning (ECCBR-04) Springer-Verlag Berlin, Heidelberg 317–330
D. McSherry (2004b) Incremental Relaxation of Unsuccessful Queries P. A. González-Calero P. Funk (Eds) Advances in Case-Based Reasoning (ECCBR-04) Springer-Verlag Berlin, Heidelberg 331–345
McSherry, D. (2005). Explanation in Recommender Systems. Artificial Intelligence Review. This Issue.
Nugent, C. & Cunningham, P. (2005). A Case-Based Explanation System for Black-Box Systems. Artificial Intelligence Review. This Issue.
Plaza, E., E. Armengol, & S. Ontañón: 2005, The Explanatory Power of Symbolic Similarity in Case-Based Reasoning. Artificial Intelligence Review. This Issue.
J. Reilly L. McCarthy K. McGinty B. Smyth (2004) Dynamic Critiquing P. A. González-Calero P. Funk (Eds) Advances in Case-Based Reasoning (ECCBR-04) Springer-Verlag Berlin, Heidelberg 763–777
Smyth, B., McGinty, L. Reilly, J. & McCarthy, K. (2004). Compound Critiques Feedback for Conversational ecommender Systems. In IEEE/WIC/ACM International Conference on Web Intelligence (WI’04), 145–151. IEEE. Beijing, China.
Sørmo, F., Cassens, J. & Aamodt, A. (2005). Explanation in Case-Based Reasoning-Perspectives & Goals. Artificial Intelligence Review. This Issue.
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Reilly, J., Mccarthy, K., Mcginty, L. et al. Explaining Compound Critiques. Artif Intell Rev 24, 199–220 (2005). https://doi.org/10.1007/s10462-005-4614-8
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DOI: https://doi.org/10.1007/s10462-005-4614-8