Abstract
Critiquing is a powerful form of feedback often used by conversational recommender systems. There are two main types of critiquing; unit and compound. Unit critiques allow the user to provide limited feedback at the feature-level by constraining a single feature’s value space. Compound critiques, on the other hand, allow the user to manipulate multiple features simultaneously and therefore can help the user to locate the product they are looking for more efficiently. However, the usefulness of the compound critiquing approach is compromised when all the options that are presented to the user are very similar to each-other. In this paper we propose the idea of presenting diverse compound critiques, and evaluate the effectiveness of two alternative approaches in terms of their recommendation performance. Specifically, we look at the degree to which critique diversity can be improved, the effect this may have on user interaction, and its expected impact on recommendation efficiency and quality
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Agrawal R., Mannila H., Srikant R., Toivonen H., Verkamo A. I. (1996). Fast Discovery of Association Rules in Large Databases. Advances in Knowledge Discovery and Data Mining 307–328
Bradley K., Smyth B. (2001). Improving Recommendation Diversity. In D. O’Donoghue (ed.) Proceedings of the 12 National Conference in Artificial Intelligence and Cognitive Science (AICS-01), 75–84, Maynooth, Ireland
Bridge D. (2002). Diverse Product Recommendations using an Expressive Language for Case Retrieval. In: Craw S., Pearce A (eds). Proceedings of the Sixth European Conference on Case-Based Reasoning (ECCBR 2002). Springer, Aberdeen, Scotland, pp. 42–57
Burke R., Hammond K., Young B. (1996). Knowledge-Based Navigation of Complex Information Spaces. In Proceedings of the 13 National Conference on Artificial Intelligence. AAAI Press/MIT Press, Portland, OR, pp. 462–468
Burke R., Hammond K., Young B. (1997). The FindMe Approach to Assisted Browsing. Journal of IEEE Expert 12(4):32–40
McCarthy K., Reilly J., McGinty L., Smyth B. (2004a). On the Dynamic Generation of Compound Critiques in Conversational Recommender Systems. In: Bra P.D (eds). Proceedings of the Third International Conference on Adaptive Hypermedia and Web-Based Systems (AH-04). Springer, Eindhoven, The Netherlands
McCarthy K., Reilly J., McGinty L., Smyth B. (2004b). Thinking Positively – Explanatory Feedback for Conversational Recommender Systems. In European Conference on Case-Based Reasoning (ECCBR-04) Explanation Workshop, Madrid, Spain
McCarthy K., Reilly J., Smyth B. (2004c). On the Generation of Diverse Compound Critiques. In: McGinty L., Crean B (eds). Proceedings of the 15 Artificial Intelligence and Cognitive Science Conference (AICS-04). Ireland, Castlebar, pp. 117–126
McGinty L., Smyth B. (2003a). On the Role of Diversity in Conversational Recommender Systems. In: Bridge D., Ashley K (eds.) Proceedings of the Fifth International Conference on Case-Based Reasoning (ICCBR-03). Springer, Troindheim Norway
McGinty L., Smyth B. (2003b). Tweaking Critiquing. In Proceedings of the Workshop on Personalization and Web Techniques at the International Joint Conference on Artificial Intelligence (IJCAI-03), Acapulco, Mexico: Morgan-Kaufmann
McSherry D. (2001). Increasing Recommendation Diversity Without Loss of Similarity. In Proceedings of the Sixth UK Workshop on Case-Based Reasoning, 23–31, Cambridge, UK
McSherry D. (2002). Diversity-Conscious Retrieval. In: Craw S (eds). Proceedings of the Sixth European Conference on Case-Based Reasoning (ECCBR-02). Springer, Aberdeen, Scotland, pp. 219–233
O’Sullivan, D., Wilson, D. & Smyth, B. (2003). Preserving Recommender Accuracy and Diversity in Sparse Datasets. In I. Russell & S. M. Haller (eds.) Proceedings of the 16 International FLAIRS Conference (FLAIRS 2003), 139–143, Florida, USA
Reilly J., McCarthy K., McGinty L., Smyth B. (2004). Dynamic Critiquing. In: Calero P.G., Funk P (eds). Proceedings of the Seventh European Conference on Case-Based Reasoning (ECCBR-04). Springer, Madrid Spain, pp. 763–777
Shimazu H. (2001). ExpertClerk: Navigating Shoppers’ Buying Process with the Combination of Asking and Proposing. In: Nebel B (eds). Proceedings of the 17 International Joint Conference on Artificial Intelligence (IJCAI-01). Morgan Kaufmann, Seattle, Washington, USA, pp. 1443–1448
Shimazu H., Shibata A., Nihei K. (2002). ExpertGuide: A Conversational Case-Based Reasoning Tool for Developing Mentors in Knowledge Spaces. Applied Intelligence 14(1):33–48
Smyth B., McClave P. (2001). Similarity vs Diversity. In: Aha D., Watson I (eds). Proceedings of the Fourth International Conference on Case-Based Reasoning (ICCBR-01). Springer, Vancouver, Canada, pp. 347–361
Smyth B., McGinty L. (2003). An Analysis of Feedback Strategies in Conversational Recommender Systems. In: Cunningham P (eds). Proceedings of the 14 National Conference on Artificial Intelligence and Cognitive Science (AICS-2003). Dublin, Ireland, pp. 211–216
Smyth B., McGinty L., Reilly J., McCarthy K. (2004). Compound Critiques for Conversational Recommender Systems. In: Zhong N., Tirri H., Yao Y., Zhou L., Liu J., Cerrone N (eds). Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI 2004). 145–151, Beijing, China.
Zhang L., Coenen F., Leng P.H. (2002). An Experimental Study of Increasing Diversity for Case-Based Diagnosis. In S. Craw & A. D. Preece (eds.) Proceedings of the Sixth European Conference on Case-Based Reasoning (ECCBR 2002), 448–459, Aberdeen, UK
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Mccarthy, K., Reilly, J., Smyth, B. et al. Generating Diverse Compound Critiques. Artif Intell Rev 24, 339–357 (2005). https://doi.org/10.1007/s10462-005-9013-7
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DOI: https://doi.org/10.1007/s10462-005-9013-7