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Université de Fribourg

Prediction in complex systems: the case of the international trade network

Vidmer, Alexandre ; Zeng, An ; Medo, Matúš ; Zhang, Yi-Cheng

In: Physica A: Statistical Mechanics and its Applications, 2015, vol. 436, p. 188–199

Predicting the future evolution of complex systems is one of the main challenges in complexity science. Based on a current snapshot of a network, link prediction algorithms aim to predict its future evolution. We apply here link prediction algorithms to data on the international trade between countries. This data can be represented as a complex network where links connect countries with the...

Université de Fribourg

Empirical comparison of local structural similarity indices for collaborative-filtering-based recommender systems

Zhang, Qian-Ming ; Shang, Ming-Sheng ; Zeng, Wei ; Chen, Yong ; Lü, Linyuan

In: Physics Procedia, 2010, vol. 3, no. 5, p. 1887-1896

Collaborative filtering is one of the most successful recommendation techniques, which can effectively predict the possible future likes of users based on their past preferences. The key problem of this method is how to define the similarity between users. A standard approach is using the correlation between the ratings that two users give to a set of objects, such as Cosine index and Pearson...