Ultra accurate collaborative information filtering via directed user similarity

A key challenge of the collaborative filtering (CF) information filtering is how to obtain the reliable and accurate results with the help of peers' recommendation. Since the similarities from small-degree users to large-degree users would be larger than the ones opposite direction, the large-degree users' selections are recommended extensively by the traditional second-order CF algorithms. By considering the users' similarity direction and the second-order correlations to depress the influence of mainstream preferences, we present the directed second-order CF (HDCF) algorithm specifically to address the challenge of accuracy and diversity of the CF algorithm. The numerical results for two benchmark data sets, MovieLens and Netflix, show that the accuracy of the new algorithm outperforms the state-of-the-art CF algorithms. Comparing with the CF algorithm based on random-walks proposed in the Ref.7, the average ranking score could reach 0.0767 and 0.0402, which is enhanced by 27.3\% and 19.1\% for MovieLens and Netflix respectively. In addition, the diversity, precision and recall are also enhanced greatly. Without relying on any context-specific information, tuning the similarity direction of CF algorithms could obtain accurate and diverse recommendations. This work suggests that the user similarity direction is an important factor to improve the personalized recommendation performance.Comment: 6 pages, 4 figure

Locating influential nodes via dynamics-sensitive centrality

With great theoretical and practical significance, locating influential nodes of complex networks is a promising issues. In this paper, we propose a dynamics-sensitive (DS) centrality that integrates topological features and dynamical properties. The DS centrality can be directly applied in locating influential spreaders. According to the empirical results on four real networks for both susceptible-infected-recovered (SIR) and susceptible-infected (SI) spreading models, the DS centrality is much more accurate than degree, $k$-shell index and eigenvector centrality.Comment: 6 pages, 1 table and 2 figure

Spin-orbit coupling induced Mott transition in Ca2−x_{2-x}Srx_{x}RuO4_{4} (0<x<0.2)

We propose a new mechanism for the paramagnetic metal-insulator transition in the layered perovskite Ca$_{2-x}$Sr$_{x}$RuO$_{4}$ (0<x<0.2). The LDA+U approach including spin-orbit coupling is used to calculate the electronic structures. In Ca$_{2}$RuO$_{4}$, we show that the spin-orbit effect is strongly enhanced by the Coulomb repulsion, which leads to an insulating phase. When Ca is substituted by Sr, the effective spin-orbit splitting is reduced due to the increasing bandwidth of the degenerate $d_{xz}$ and $d_{yz}$ orbitals. For x=0.2, the compound is found to be metallic. We show that these results are in good agreement with the experimental phase diagram.Comment: 4 pages, 4 figure