In: International Journal of Modern Physics C, 2009, vol. 20, no. 12, p. 1925-1932
In this paper, based on a weighted projection of the user-object bipartite network, we study the effects of user tastes on the mass-diffusion-based personalized recommendation algorithm, where a user's tastes or interests are defined by the average degree of the objects he has collected. We argue that the initial recommendation power located on the objects should be determined by both of their...
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In: Physica A: Statistical Mechanics and its Applications, 2008, vol. 387, no. 22, p. 5523-5534
A simple trading model based on pair pattern strategy space with holding periods is proposed. Power-law behavior is observed for the return variance σ², the price impact H and the predictability K for both models, with linear and square root impact functions. The sum of the traders’ wealth displays a positive value for the model with a square root price impact function,...
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In: Europhysics Letters, 2007, vol. 80, no. 6, p. 68003
Information overload in the modern society calls for highly efficient recommendation algorithms. In this letter we present a novel diffusion-based recommendation model, with users' ratings built into a transition matrix. To speed up computation we introduce a Green function method. The numerical tests on a benchmark database show that our prediction is superior to the standard recommendation...
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In: Europhysics Letters, 2008, vol. 82, no. 5, p. 58007
Recommender systems are significant to help people deal with the world of information explosion and overload. In this letter, we develop a general framework named self-consistent refinement and implement it by embedding two representative recommendation algorithms: similarity-based and spectrum-based methods. Numerical simulations on a benchmark data set demonstrate that the present method...
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In: Europhysics Letters, 2008, vol. 81, no. 5, p. 58004
In this paper, based on a weighted object network, we propose a recommendation algorithm, which is sensitive to the configuration of initial resource distribution. Even under the simplest case with binary resource, the current algorithm has remarkably higher accuracy than the widely applied global ranking method and collaborative filtering. Furthermore, we introduce a free parameter β to...
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In: Physical Review Letters, 2007, vol. 99, no. 15, p. 154301
Using heat conduction mechanism on a social network we develop a systematic method to predict missing values as recommendations. This method can treat very large matrices that are typical of internet communities. In particular, with an innovative, exact formulation that accommodates arbitrary boundary condition, our method is easy to use in real applications. The performance is assessed by...
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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, 2006, vol. 365, no. 2, p. 529-542
Minority games where groups of agents remember, react or incorporate information with different timescales are investigated. We support our findings by analytical arguments whenever possible.
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In: Physica A: Statistical and Theoretical Physics, 2007, vol. 373, no. 1, p. 753-758
We develop a simple statistical method to find affinity relations in a large opinion network which is represented by a very sparse matrix. These relations allow us to predict missing matrix elements. We test our method on the Eachmovie data of thousands of movies and viewers. We found that significant prediction precision can be achieved and it is rather stable. There is an intrinsic limit to...
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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...
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