Abstract
In conversational collaborative recommender systems, user feedback influences the recommendations. We report mechanisms for enhancing the diversity of the recommendations made by collaborative recommenders. We focus on techniques for increasing diversity that rely on collaborative data only. In our experiments, we compare different mechanisms and show that, if recommendations are diverse, users find target items in many fewer recommendation cycles.
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References
Balabanović M and Shoham Y (1997). Fab: content-based, collaborative recommendation. Communications of the ACM 40(3): 66–72
Bradley K, Smyth B (2001) Improving recommendation diversity. In: O’Donoghue D (ed) Proceedings of the 12th Irish conference on artificial intelligence and cognitive science. NUI Maynooth, pp 85–94
Bridge D, Ferguson A (2002) Diverse product recommendations using an expressive language for case retrieval. In: Craw S, Preece A (eds) Proceedings of the 6th European conference on case-based reasoning. Springer, pp 43–57
Bridge D, Göker MH, McGinty L and Smyth B (2006). Case-based recommender systems. Knowledge Engineering Review 20(3): 315–320
Bridge D, Kelly JP (2005) Diversity-enhanced conversational collaborative recommendations. In: Creaney N (ed) Proceedings of the 16th Irish conference on artificial intelligence & cognitive science. University of Ulster, pp 29–38
Burke RD, Hammond KJ and Young BC (1997). The findme approach to assisted browsing. IEEE Expert 12(5): 32–40
Doyle M, Cunningham P (2000) A dynamic approach to reducing dialog in on-line decision guides. In: Blanzieri E, Portinale L (eds) Proceedings of the 5th European workshop on case-based reasoning. Trento, Italy, Springer: pp 49–60
Herlocker J, Konstan JA, Terveen LG and Riedl JT (2004). Evaluating collaborative filtering recommender systems. ACM Transactions on Information Systems 22(1): 5–53
Herlocker JL (2000) Understanding and improving automated collaborative filtering systems. Ph.D. thesis, University of Minnesota
Linden, G, Hanks S, Lesh N (1997) Interactive assessment of user preference models: the automated travel assistant. In: Jameson A, Paris C, Tasso C (eds) Proceedings of the 6th international conference on user modeling. Springer, pp 67–78
McGinty L, Smyth B (2002) Comparison-based recommendation. In: Craw S, Preece A (eds) Proceedings of the 6th European conference on case-based reasoning. Aberdeen, Scotland, Springer, pp 575–589
McGinty L, Smyth B (2003) On the role of diversity in conversational recommender systems. In: Ashley K, Bridge D (eds) Proceedings of the 5th international conference on case-based reasoning. Springer, pp 276–290
McSherry D (2002) Diversity-conscious retrieval. In: Craw S, Preece A (eds) Proceedings of the 6th European conference on case-based reasoning. Springer, pp 219–233
Pu P, Viappiani P, Faltings B (2006) Increasing user decision accuracy using suggestions. In: Grinter R et al (eds) Proceedings of the conference on human factors in computing systems (CHI). ACM Press, pp 121–130
Rafter R, Smyth B (2004) Towards conversational collaborative filtering. In: McGinty L, Crean B (eds) Proceedings of the 15th artificial intelligence and cognitive science conference. pp 147–156
Reilly J, McCarthy K, McGinty L, Smyth B (2004) Dynamic critiquing. In: Funk P, González-Calero PA (eds) Proceedings of the 7th European conference on case-based reasoning. Madrid, Spain, Springer, pp 763–777
Resnick P and Varian HR (1997). Recommender systems. Communications of the ACM 40(3): 56–58
Riedl J, Konstan J (2002) Word of mouse: the marketing power of collaborative filtering. Warner Books
Sarwar BM, Karypis G, Konstan JA, Riedl J (2001) Item-based collaborative filtering recommendation algorithms. In: Proceedings of the 10th international world Wide Web Conference. pp 285–295
Schmitt S (2002). simVar; A similarity-influenced question selection criterion for e-sales dialogs. Artificial Intelligence Review 18(3–4): 195–221
Shimazu H (2002). ExpertClerk: a conversational case-based reasoning tool for developing salesclerk agents in E-Commerce webshops. Artificial Intelligence Review 18(3–4): 223–244
Smyth B, McClave P (2001) Similarity vs. diversity. In: Aha DW, Watson I (eds) Proceedings of the 4th international conference on case-based reasoning. Springer, pp 347–361
Ziegler C-N, McNee SM, Konstan JA, Lausen G (2005) Improving recommendation lists through topic diversification. In: Proceedings of the 14th international World Wide Web Conference. ACM Press, pp 22–32
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Kelly, J.P., Bridge, D. Enhancing the diversity of conversational collaborative recommendations: a comparison. Artif Intell Rev 25, 79–95 (2006). https://doi.org/10.1007/s10462-007-9023-8
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DOI: https://doi.org/10.1007/s10462-007-9023-8