In: Europhysics Letters, 2009, vol. 88, no. 3, p. 38005
Most news recommender systems try to identify users' interests and news' attributes and use them to obtain recommendations. Here we propose an adaptive model which combines similarities in users' rating patterns with epidemic-like spreading of news on an evolving network. We study the model by computer agent-based simulations, measure its performance and discuss its robustness against bias and...
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In: Quantitative Finance, 2010, vol. 10, no. 7, p. 689-697
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Thèse de doctorat : Université de Fribourg, 2008 ; no 1614.
Knowledge and information make our lives easier and more enjoyable. In this thesis we use techniques and concepts from statistical physics and probability theory to explore several models of complex systems where information plays a prominent role. When building these models we tried to capture main aspects of real systems but also to keep the models simple and analytically solvable. We begin the...
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In: Physical Review E, 2007, vol. 76, no. 4, p. 046115
One-mode projecting is extensively used to compress bipartite networks. Since one-mode projection is always less informative than the bipartite representation, a proper weighting method is required to better retain the original information. In this article, inspired by the network-based resource-allocation dynamics, we raise a weighting method which can be directly applied in extracting the...
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In: Journal of Statistical Mechanics, 2009, vol. 2009, no. 2, p. P02014
One of the key socioeconomic phenomena to explain is the distribution of wealth. Bouchaud and Mézard (2000 Physica A 282 536) have proposed an interesting model of an economy based on trade and investments of agents. In the mean-field approximation, the model produces a stationary wealth distribution with a power law tail. In this paper we examine characteristic timescales of the model and...
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In: EPL (Europhysics Letters), 2013, vol. 101, no. 2, p. 20008
Recommender systems recommend objects regardless of potential adverse effects of their overcrowding. We address this shortcoming by introducing crowd-avoiding recommendation where each object can be shared by only a limited number of users or where object utility diminishes with the number of users sharing it. We use real data to show that contrary to expectations, the introduction of these...
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In: Journal of Informetrics, 2019, vol. 13, no. 2, p. 717–725
Identifying the future influential papers among the newly published ones is an important yet challenging issue in bibliometrics. As newly published papers have no or limited citation history, linear extrapolation of their citation counts—which is motivated by the well-known preferential attachment mechanism—is not applicable. We translate the recently introduced notion of discoverers to...
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In: Physica A: Statistical Mechanics and its Applications, 2008, vol. 387, no. 24, p. 6151-6158
Financial markets, with their vast range of different investment opportunities, can be seen as a system of many different simultaneous games with diverse and often unknown levels of risk and reward. We introduce generalizations to the classic Kelly investment game [J.L. Kelly, IEEE Transactions on Information Theory 2 (1956) 185–189] that incorporates these features, and use them to investigate...
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In: The European Physical Journal B, 2013, vol. 86, no. 6, p. 1-7
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In: The European Physical Journal B, 2013, vol. 86, no. 6, p. 1-7
The classical preferential attachment model is sensitive to the choice of the initial configuration of the network. As the number of initial nodes and their degree grow, so does the time needed for an equilibrium degree distribution to be established. We study this phenomenon, provide estimates of the equilibration time, and characterize the degree distribution cutoff observed at finite times....
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