Abstract
This thesis investigates the properties of a good explanation in a movie recommender system. Beginning with a summarized literature review, we suggest seven criteria for evaluation of explanations in recommender systems. This is followed by an attempt to define the properties of a useful explanation, using a movie review corpus and focus groups. We conclude with planned experiments and evaluation.
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References
Buchanan, B.G., Shortliffe, E.H. (eds.): 30-35. In: The Rule-Based Expert Systems: The MYCIN Experiments of the Stanford Heuristic Programming Project, pp. 571–665 Addison-Wesley Publishing Company (1985)
Doyle, D., Tsymbal, A., Cunningham, P.: A review of explanation and explanation in case-based reasoning. Technical report, Department of Computer Science, Trinity College, Dublin (2003)
Druzdzel, M.J.: Qualitative verbal explanations in bayesian belief networks. Artificial Intelligence and Simulation of Behaviour Quarterly, special issue on Bayesian networks, pp. 43–54 (1996)
Bilgic, M., Mooney, R.J.: Explaining recommendations: Satisfaction vs. promotion. In: Beyond Personalization Workshop, IUI (2005)
Herlocker, J.L., Konstan, J.A., Riedl, J.: Explaining collaborative filtering recommendations. In: Computer Supported Cooperative Work (2000)
Mcsherry, D.: Explanation in recommender systems. Artificial Intelligence Review 24(2), 179–197 (2005)
Tintarev, N., Masthoff, J.: A survey of explanations in recommender systems. In: WPRSIUI associated with ICDE (2007)
McNee, S.M., Riedl, J., Konstan, J.A.: Being accurate is not enough: How accuracy metrics have hurt recommender systems. In: Extended Abstracts of CHI (2006)
Ziegler, C.N., McNee, S.M., Konstan, J.A., Lausen, G.: Improving recommendation lists through topic diversification. In: WWW 2005 (2005)
Chen, L., Pu, P.: Trust building in recommender agents. In: WPRSIU 2002 (2002)
Carenini, G.J., Moore, J.: An empirical study of the influence of argument conciseness on argument effectiveness. In: Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics (2000)
Sinha, R., Swearingen, K.: The role of transparency in recommender systems. In: Conference on Human Factors in Computing Systems (2002)
Czarkowski, M.: Evaluating scrutable adaptive hypertext. In: 10th International Conference on User Modeling, Workshop 3: Evaluation of Adaptive Systems (2005)
Swearingen, K., Sinha, R.: Interaction design for recommender systems. In: Designing Interactive Systems (2002)
Thompson, C.A., Göker, M.H., Langley, P.: A personalized system for conversational recommendations. J. Artif. Intell. Res (JAIR) 21, 393–428 (2004)
Sinha, R., Swearingen, K.: Comparing recommendations made by online systems and friends. In: DELOS-NSF Workshop on Personalization and Recommender Systems in Digital Libraries (2001)
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Tintarev, N. (2007). Explaining Recommendations. In: Conati, C., McCoy, K., Paliouras, G. (eds) User Modeling 2007. UM 2007. Lecture Notes in Computer Science(), vol 4511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73078-1_67
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DOI: https://doi.org/10.1007/978-3-540-73078-1_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-73077-4
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