In: New Journal of Physics, 2009, vol. 11, p. 123008
In this paper, based on a weighted projection of a bipartite user-object network, we introduce a personalized recommendation algorithm, called network-based inference (NBI), which has higher accuracy than the classical algorithm, namely collaborative filtering. In NBI, the correlation resulting from a specific attribute may be repeatedly counted in the cumulative recommendations from different...
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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: The European Physical Journal B, 2013, vol. 86, no. 2, p. 1-8
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In: The European Physical Journal B, 2013, vol. 86, no. 2, p. 1-8
People in the Internet era have to cope with the information overload, striving to find what they are interested in, and usually face this situation by following a limited number of sources or friends that best match their interests. A recent line of research, namely adaptive social recommendation, has therefore emerged to optimize the information propagation in social networks and provide...
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In: Physica A: Statistical Mechanics and its Applications, 2005, vol. 345, no. 3-4, p. 705-712
We analyze some voting models mimicking online evaluation systems intended to reduce the information overload. The minimum number of operations needed for a system to be effective is analytically estimated. When herding effects are present, linear preferential attachment marks a transition between trustful and biased reputations.
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In: Physica A: Statistical Mechanics and its Applications, 2016, vol. 444, p. 397–402
Bipartite matching problems emerge in many human social phenomena. In this paper, we study the ground state of the Gale–Shapley model, which is the most popular bipartite matching model. We apply the Kuhn–Munkres algorithm to compute the numerical ground state of the model. For the first time, we obtain the number of blocking pairs which is a measure of the system instability. We also show...
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In: Quantitative Finance, 2010, vol. 10, no. 7, p. 689-697
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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: Physica A: Statistical Mechanics and its Applications, 2009, vol. 388, no. 23, p. 4867-4871
In this paper, by applying a diffusion process, we propose a new index to quantify the similarity between two users in a user–object bipartite graph. To deal with the discrete ratings on objects, we use a multi-channel representation where each object is mapped to several channels with the number of channels being equal to the number of different ratings. Each channel represents a certain...
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In: Physica A: Statistical Mechanics and its Applications, 2018, vol. 499, p. 490–497
Understanding the patterns of collective behavior in online social network (OSNs) is critical to expanding the knowledge of human behavior and tie relationship. In this paper, we investigate a specific pattern called social signature in Facebook and Wiki users’ online communication behaviors, capturing the distribution of frequency of interactions between different alters over time in the...
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