Abstract
Current generation recommender systems are considered to be limited in: (1) utilizing users’ qualitative choices and (2) tackling new items and new users. Our research focuses on building a new recommender system that utilizes users’ qualitative and conditional preferences with Collaborative Filtering (CF). We call it CF with Conditional Preferences (CFCP). To represent users’ conditional preferences in CFCP, we have developed Probabilistic TCP-net (PTCP-net). Intuitively, we argue that CFCP will be able to overcome the existing limitations, however we plan to do in-depth research on it.
Author’s PhD research is supervised and supported by Dr. Malek Mouhoub, Professor, Department of Computer Science, University of Regina, Canada.
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References
Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734–749 (2005)
Boutilier, C., Brafman, R.I., Domshlak, C., Hoos, H.H., Poole, D.: CP-nets: a tool for representing and reasoning with conditional ceteris paribus preference statements. J. Artif. Intell. Res. 21, 135–191 (2004)
Brafman, R.I., Domshlak, C., Shimony, S.E.: On graphical modeling of preference and importance. J. Artif. Intell. Res. 25(1), 389–424 (2006)
Breese, J.S., Heckerman, D., Kadie, C.: Empirical analysis of predictive algorithms for collaborative filtering. In: 14th Conference on Uncertainty in Artificial Intelligence, pp. 43–52 (1998)
Burke, R., Felfernig, A., Gker, M.H.: Recommender systems: an overview. AI Mag. 32(3), 13–18 (2011)
Jin, R., Si, L., Zhai, C.X.: Preference-based graphic models for collaborative filtering. In: 19th Conference on Uncertainty in Artificial Intelligence, pp. 329–336 (2003)
Konstan, J.A., Miller, B.N., Maltz, D., Herlocker, J.L., Gordon, L.R., Riedl, J.: GroupLens: applying collaborative filtering to usenet news. Commun. ACM 40(3), 77–87 (1997)
Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann Publishers Inc., San Francisco (1988)
Resnick, P., Iacovou, N., Suchak, M., Bergstrom, P., Riedl, J.: GroupLens: an open architecture for collaborative filtering of netnews. In: Proceedings of ACM Conference on Computer Supported Cooperative Work, pp. 175–186 (1994)
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Ahmed, S. (2017). Collaborative Filtering with Users’ Qualitative and Conditional Preferences. In: Mouhoub, M., Langlais, P. (eds) Advances in Artificial Intelligence. Canadian AI 2017. Lecture Notes in Computer Science(), vol 10233. Springer, Cham. https://doi.org/10.1007/978-3-319-57351-9_45
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DOI: https://doi.org/10.1007/978-3-319-57351-9_45
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