Abstract
Conversational recommender systems adapt the sets of products they recommend in light of user feedback. Our contribution here is to devise and compare four different mechanisms for enhancing the diversity of the recommendations made by collaborative recommenders. Significantly, we increase diversity using collaborative data only. We find that measuring the distance between products using Hamming Distance is more effective than using Inverse Pearson Correlation.
This material is based on works supported by Science Foundation Ireland under Grant No. 03/IN.3/136. We are grateful to Professor Barry Smyth for his advice and to the GroupLens project team for making their data available.
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Rafter, R., Smyth, B.: Towards conversational collaborative filtering. In: McGinty, L., Crean, B. (eds.) Procs. of the 15th Artificial Intelligence and Cognitive Science Conference, pp. 147–156 (2004)
Herlocker, J.L.: Understanding and Improving Automated Collaborative Filtering Systems. Ph.D thesis, University of Minnesota (2000)
Bridge, D., Kelly, J.P.: Diversity-enhanced conversational collaborative recommendations. In: Creaney, N. (ed.) Procs. of the 16th Irish Conference on Artificial Intelligence & Cognitive Science, University of Ulster, pp. 29–38 (2005)
Smyth, B., McClave, P.: Similarity vs. diversity. In: Aha, D.W., Watson, I. (eds.) Procs. of the 4th International Conference on Case-Based Reasoning, pp. 347–361. Springer, Heidelberg (2001)
Bridge, D., Ferguson, A.: Diverse product recommendations using an expressive language for case retrieval. In: Craw, S., Preece, A. (eds.) Procs. of the 6th European Conference on Case-Based Reasoning, pp. 43–57. Springer, Heidelberg (2002)
McSherry, D.: Diversity-conscious retrieval. In: Craw, S., Preece, A. (eds.) Procs. of the 6th European Conference on Case-Based Reasoning, pp. 219–233. Springer, Heidelberg (2002)
Ziegler, C.-N., McNee, S.M., Konstan, J.A., Lausen, G.: Improving recommendation lists through topic diversification. In: Procs. of the 14th International World Wide Web Conference, pp. 22–32. ACM Press, New York (2005)
McGinty, L., Smyth, B.: On the role of diversity in conversational recommender systems. In: Ashley, K., Bridge, D. (eds.) Procs. of the 5th International Conference on Case-Based Reasoning, pp. 276–290. Springer, Heidelberg (2003)
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Bridge, D., Kelly, J.P. (2006). Ways of Computing Diverse Collaborative Recommendations. In: Wade, V.P., Ashman, H., Smyth, B. (eds) Adaptive Hypermedia and Adaptive Web-Based Systems. AH 2006. Lecture Notes in Computer Science, vol 4018. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11768012_6
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DOI: https://doi.org/10.1007/11768012_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34696-8
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