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Université de Fribourg

Solving the apparent diversity-accuracy dilemma of recommender systems

Zhou, Tao ; Kuscsik, Zoltán ; Liu, Jian-Guo ; Medo, Matúš ; Wakeling, Joseph Rushton ; Zhang, Yi-Cheng

In: Proceedings of the National Academy of Sciences of the USA - PNAS, 2010, vol. 107, no. 10, p. 4511-4515

Recommender systems use data on past user preferences to predict possible future likes and interests. A key challenge is that while the most useful individual recommendations are to be found among diverse niche objects, the most reliably accurate results are obtained by methods that recommend objects based on user or object similarity. In this paper we introduce a new algorithm specifically to...

Université de Fribourg

Decoding information from noisy, redundant, and intentionally distorted sources

Yu, Yi-Kuo ; Zhang, Yi-Cheng ; Laureti, Paolo ; Moret, Lionel

In: Physica A: Statistical and Theoretical Physics, 2006, vol. 371, no. 2, p. 732-744

Advances in information technology reduce barriers to information propagation, but at the same time they also induce the information overload problem. For the making of various decisions, mere digestion of the relevant information has become a daunting task due to the massive amount of information available. This information, such as that generated by evaluation systems developed by various web...

Université de Fribourg

Selection by pairwise comparisons with limited resources

Laureti, Paolo ; Mathiesen, Joachim ; Zhang, Yi-Cheng

In: Physica A: Statistical Mechanics and its Applications, 2004, vol. 338, p. 596-604

We analyze different methods of sorting and selecting a set of objects by their intrinsic value, via pairwise comparisons whose outcome is uncertain. After discussing the limits of repeated Round Robins, two new methods are presented: The ran-fil requires no previous knowledge on the set under consideration, yet displaying good performances even in the least favorable case. The min-ent method...