Comparison-Based Recommendation*

Lorraine Mc Ginty1 and Barry Smyth1,2

1 Smart Media Institute, University College Dublin, Dublin 4, Ireland.
Lorraine.McGinty@ucd.ie
2 ChangingWorlds Ltd., South County Business Park, Dublin 18, Ireland.
Barry.Srnyth@ChangingWorlds.com




Abstract. Recommender systems combine user profiling and filtering
techniques to provide more pro-active and personal information retrieval
systems, and have been gaining in popularity as a way of overcoming the
ubiquitous information overload problem. Many recommender systems
operate as interactive systems that seek feedback from the end-user as
part of the recommendation process to revise the users query. In this
paper we examine different forms of feedback that have been used in the
past and focus on a low-cost preference-based feedback model, which to
date has been very much under utilised. In particular we describe and
evaluate a novel comparison-based recommendation framework which is
designed to utilise preference-based feedback. Specifically, we present results 
that highlight the benefits of a number of new query revision strategies 
and evidence to suggest that the popular more-like-this strategy may
be flawed.
References

1.	D.W. Aha, L.A. Breslow, and H. Muoz-Avila. Conversational case-based reasoning. 
Applied Intelligence, 14:932, 2000.
2.	M. Balabanovic and Y. Shoham. FAB: Content-Based Collaborative Recommender. 
Communications of the ACM, 40(3):6672, 1997.
3.	K. Bradley and B. Smyth. Improving Recommendation Diversity. In
D. ODonoghue, editor, Proceedings of the Twelfth National Conference in Artificial 
Intelligence and Cognitive Science (AICS-01), pages 7584, 2001. Maynooth,
Ireland.
4.	D. Bridge. Product Recommendation Systems: A New Direction. In D. Aha and
I. Watson, editors, Workshop on CBR in Electronic Commerce at The International
Conference on Case-Based Reasoning (ICCBR-01), 2001. Vancouver, Canada.
5.	R. Burke, K. Hammond, and B.C. Young. The FindMe Approach to Assisted
Browsing. Journal of IEEE Expert, 12(4):3240, 1997.
6.	M. Doyle and P. Cunningham. A Dynamic Approach to Reducing Dialog in On-Line 
Decision Guides. In E. Blanzieri and L. Portinale, editors, Proceedings of the
Fifth European Workshop on Case-Based Reasoning, EWCBR-2000, pages 4960.
Springer, 2000. Trento, Italy.
7.	M. Goker and C. Thompson. Personalized Conversational Case-based Recommendation. 
In E. Blanzieri and L. Portinale, editors, Advances in Case-Based Reasoning: 
Proceedings of the Fifth European Workshop on Case-based Reasoning, pages
99-111. Springer-Verlag, 2000.
8.	A. Kohlmaier, S. Schmitt, and R. Bergmann. Evaluation of a Similarity-based Approach 
to Customer-adaptive Electronic Sales Dialogs. In S. Weibelzahl, D. Chin,
and G. Weber, editors, Empirical Evaluation of Adaptive Systems. Proceedings of
the workshop held at the 8th International Conference on User Modelling, pages
4050, 2001. Sonthofen, Germany.
9.	L. McGinty and B. Smyth. Collaborative Case-Based Reasoning: Applications in
Personalised Route Planning. In D. Aha and I. Watson, editors, Proceedings of the
International Conference on Case-Based Reasoning (ICCBR-01), pages 362376.
Springer-Verlag, 2001. Vancouver, Canada.
10.	J.R. Quinlan. Induction of decision trees. Journal of Machine Learning, 1:81106,
1986.
11.	H. Shimazu. ExpertClerk : Navigating Shoppers Buying Process with the Combination 
of Asking and Proposing. In Bernhard Nebel, editor, Proceedings of the Seventeenth 
International Joint Conference on Artificial Intelligence (IJCAI-2001),
pages Volume 2, pages 14431448. Morgan Kaufmann, 2001. Seattle, Washington.
12.	B. Smyth and P. Cotter. A Personalized TV Listings Service for the Digital TV
Age. Journal of Knowledge-Based Systems, 13(2-3) :5359, 2000.
13.	B. Smyth and P. Cunningham. A Comparison of Incremental Case-Based Reasoning 
and Inductive Learning. In Proceedings of the Second European Workshop on
Case-Based Reasoning, EWCBR-94. Springer, 1994. Chantilly, France.
14.	B. Smyth and P. McClave. Similarity vs Diversity. In D. Aha and I. Watson, editors, 
Proceedings of the International Conference on Case-Based Reasoning, pages
347361. Springer, 2001.
