arXiv subjects

Tao Zhou

Publications and source records attributed to Tao Zhou.

At least 487 records · Page 27Linked to original sources

arXiv2011

Link prediction in complex networks: a local na\"ıve Bayes model

Common-neighbor-based method is simple yet effective to predict missing links, which assume that two nodes are more likely to be connected if they have more common neighbors. In such method, each common neighbor of two nodes contributes equally to the connection likelihood. In this Letter, we argue that different common neighbors may play different roles and thus lead to different contributions, and propose a local na\"ıve Bayes model accordingly. Extensive experiments were carried out on eight real networks. Compared with the common-neighbor-based methods, the present method can provide more accurate predictions. Finally, we gave a detailed case study on the US air transportation network.

physics.soc-ph↗

arXiv2011

Consistent picture for the electronic structure around a vortex core in iron-based superconductors

Based on a two-orbital model and taking into account the presence of the impurity, we studied theoretically the electronic structure in the vortex core of the iron-Pnictide superconducting materials. The vortex is pinned when the impurity is close to the vortex core. The bound states shows up for the unpinned vortex and are wiped out by a impurity. Our results are in good agreement with recent experiments and present a consistent explanation for the different electronic structure of vortex core revealed by experiments on different materials.

cond-mat.supr-con↗

arXiv2011

Emergence of scale-free leadership structure in social recommender systems

The study of the organization of social networks is important for understanding of opinion formation, rumor spreading, and the emergence of trends and fashion. This paper reports empirical analysis of networks extracted from four leading sites with social functionality (Delicious, Flickr, Twitter and YouTube) and shows that they all display a scale-free leadership structure. To reproduce this feature, we propose an adaptive network model driven by social recommending. Artificial agent-based simulations of this model highlight a "good get richer" mechanism where users with broad interests and good judgments are likely to become popular leaders for the others. Simulations also indicate that the studied social recommendation mechanism can gradually improve the user experience by adapting to tastes of its users. Finally we outline implications for real online resource-sharing systems.

physics.soc-ph↗

arXiv2011

Theoretical investigation of the four-layered self-doped high-T$_c$ superconductors: evidence of pair tunneling effect

Based on a four-layered self-doped $t-J$ type model and the slave-boson mean-field approach, we study theoretically the superconductivity in the electron-doped and hole-doped layers. The neighbor layers are coupled through both the single electron interlayer hopping and pair tunneling effect. The superconducting gap magnitude for the electron-doped band is nearly twice of that of the hole-doped one, which contrasts to our previous understanding of the electron-hole asymmetry in high-T$_c$ superconductors but consistent with recent angle-resolved-photoemission-spectroscopy experiments in four-layered materials Ba$_2$Ca$_3$Cu$_4$O$_8$F$_2$. Our results propose that the pair tunneling effect is important to examine the multi-layered superconducting materials.

cond-mat.supr-con↗

arXiv2011

Leaders in Social Networks, the Delicious Case

Finding pertinent information is not limited to search engines. Online communities can amplify the influence of a small number of power users for the benefit of all other users. Users' information foraging in depth and breadth can be greatly enhanced by choosing suitable leaders. For instance in delicious.com, users subscribe to leaders' collection which lead to a deeper and wider reach not achievable with search engines. To consolidate such collective search, it is essential to utilize the leadership topology and identify influential users. Google's PageRank, as a successful search algorithm in the World Wide Web, turns out to be less effective in networks of people. We thus devise an adaptive and parameter-free algorithm, the LeaderRank, to quantify user influence. We show that LeaderRank outperforms PageRank in terms of ranking effectiveness, as well as robustness against manipulations and noisy data. These results suggest that leaders who are aware of their clout may reinforce the development of social networks, and thus the power of collective search.

physics.soc-ph↗

arXiv2011

Quasiparticle states around a nonmagnetic impurity in electron-doped iron-based superconductors with spin-density-wave order

The quasiparticle states around a nonmagnetic impurity in electron-doped iron-based superconductors with spin-density-wave (SDW) order are investigated as a function of doping and impurity scattering strength. In the undoped sample, where a pure SDW state exists, two impurity-induced resonance peaks are observed around the impurity site and they are shifted to higher (lower) energies as the strength of the positive (negative) scattering potential (SP) is increased. For the doped samples where the SDW order and the superconducting order coexist, the main feature is the existence of sharp in-gap resonance peaks whose positions and intensity depend on the strength of the SP and the doping concentration. In all cases, the local density of states exhibits clear $C_2$ symmetry. We also note that in the doped cases, the impurity will divide the system into two sublattices with distinct values of magnetic order. Here we use the band structure of a two-orbital model, which considers the asymmetry of the As atoms above and below the Fe-Fe plane. This model is suitable to study the properties of the surface layers in the iron-pnictides and should be more appropriate to describe the scanning tunneling microscopy experiments.

cond-mat.supr-con↗

arXiv2011

Efficient routing strategies in scale-free networks with limited bandwidth

We study the traffic dynamics in complex networks where each link is assigned a limited and identical bandwidth. Although the first-in-first-out (FIFO) queuing rule is widely applied in the routing protocol of information packets, here we argue that if we drop this rule, the overall throughput of the network can be remarkably enhanced. We proposed some efficient routing strategies that do not strictly obey the FIFO rule. Comparing with the routine shortest path strategy, the throughput for both Barabási-Albert (BA) networks and the real Internet, the throughput can be improved more than five times. We calculate the theoretical limitation of the throughput. In BA networks, our proposed strategy can achieve 88% of the theoretical optimum, yet for the real Internet, it is about 12%, implying that we have a huge space to further improve the routing strategy for the real Internet. Finally we discuss possibly promising ways to design more efficient routing strategies for the Internet.

physics.data-an↗

arXiv2011

Effective Mechanism for Social Recommendation of News

Recommendation systems represent an important tool for news distribution on the Internet. In this work we modify a recently proposed social recommendation model in order to deal with no explicit ratings of users on news. The model consists of a network of users which continually adapts in order to achieve an efficient news traffic. To optimize network's topology we propose different stochastic algorithms that are scalable with respect to the network's size. Agent-based simulations reveal the features and the performance of these algorithms. To overcome the resultant drawbacks of each method we introduce two improved algorithms and show that they can optimize network's topology almost as fast and effectively as other not-scalable methods that make use of much more information.

physics.soc-ph↗

arXiv2011

Scaling in the global spreading patterns of pandemic Influenza A (H1N1) and the role of control: empirical statistics and modeling

Background: The pandemic of influenza A (H1N1) is a serious on-going global public crisis. Understanding its spreading dynamics is of fundamental importance for both public health and scientific researches. Recent studies have focused mainly on evaluation and prediction of on-going spreading, which strongly depends on detailed information about the structure of social contacts, human traveling patterns and biological activity of virus, etc. Methodology/Principal Findings: In this work we analyzed the distributions of confirmed cases of influenza A (H1N1) in different levels and find the Zipf's law and Heaps' law. Similar scaling properties were also observed for severe acute respiratory syndrome (SARS) and bird cases of H5N1. We also found a hierarchical spreading pattern from countries with larger population and GDP to countries with smaller ones. We proposed a model that considers generic control effects on both the local growth and transregional transmission, without the need of the above mentioned detailed information. We studied in detail the impact of control effects and heterogeneity on the spreading dynamics in the model and showed that they are responsible for the scaling and hierarchical spreading properties observed in empirical data. Conclusions/Significance: Our analysis and modeling showed that although strict control measures for interregional travelers could delay the outbreak in the regions without local cases, the focus should be turned to local prevention after the outbreak of local cases. Target control on a few regions with the largest number of active interregional travelers can efficiently prevent the spreading. This work provided not only a deeper understanding of the generic mechanisms underlying the spread of infectious diseases, but also some practical guidelines for decision makers to adopt suitable control strategies.

physics.soc-ph↗

arXiv2010

Scaling Mobility Patterns and Collective Movements: Deterministic Walks in Lattices

Scaling mobility patterns have been widely observed for animals. In this paper, we propose a deterministic walk model to understand the scaling mobility patterns, where walkers take the least-action walks on a lattice landscape and prey. Scaling laws in the displacement distribution emerge when the amount of prey resource approaches the critical point. Around the critical point, our model generates ordered collective movements of walkers with a quasi-periodic synchronization of walkers' directions. These results indicate that the co-evolution of walkers' least-action behavior and the landscape could be a potential origin of not only the individual scaling mobility patterns, but also the flocks of animals. Our findings provide a bridge to connect the individual scaling mobility patterns and the ordered collective movements.

physics.data-an↗

arXiv2010

A robust ranking algorithm to spamming

Ranking problem of web-based rating system has attracted many attentions. A good ranking algorithm should be robust against spammer attack. Here we proposed a correlation based reputation algorithm to solve the ranking problem of such rating systems where user votes some objects with ratings. In this algorithm, reputation of user is iteratively determined by the correlation coefficient between his/her rating vector and the corresponding objects' weighted average rating vector. Comparing with iterative refinement (IR) and mean score algorithm, results for both artificial and real data indicate that, the present algorithm shows a higher robustness against spammer attack.

cs.IR↗

arXiv2010

Heterogeneity, quality, and reputation in an adaptive recommendation model

Recommender systems help people cope with the problem of information overload. A recently proposed adaptive news recommender model [Medo et al., 2009] is based on epidemic-like spreading of news in a social network. By means of agent-based simulations we study a "good get richer" feature of the model and determine which attributes are necessary for a user to play a leading role in the network. We further investigate the filtering efficiency of the model as well as its robustness against malicious and spamming behaviour. We show that incorporating user reputation in the recommendation process can substantially improve the outcome.

physics.soc-ph↗

arXiv2010

Exact solution of gyration radius of individual's trajectory for a simplified human mobility model

Gyration radius of individual's trajectory plays a key role in quantifying human mobility patterns. Of particular interests, empirical analyses suggest that the growth of gyration radius is slow versus time except the very early stage and may eventually arrive to a steady value. However, up to now, the underlying mechanism leading to such a possibly steady value has not been well understood. In this Letter, we propose a simplified human mobility model to simulate individual's daily travel with three sequential activities: commuting to workplace, going to do leisure activities and returning home. With the assumption that individual has constant travel speed and inferior limit of time at home and work, we prove that the daily moving area of an individual is an ellipse, and finally get an exact solution of the gyration radius. The analytical solution well captures the empirical observation reported in [M. C. Gonz`alez et al., Nature, 453 (2008) 779]. We also find that, in spite of the heterogeneous displacement distribution in the population level, individuals in our model have characteristic displacements, indicating a completely different mechanism to the one proposed by Song et al. [Nat. Phys. 6 (2010) 818].

physics.soc-ph↗

arXiv2010

Modeling correlated human dynamics

We empirically study the activity patterns of individual blog-posting and find significant memory effects. The memory coefficient first decays in a power law and then turns to an exponential form. Moreover, the inter-event time distribution displays a heavy-tailed nature with power-law exponent dependent on the activity. Our findings challenge the priority-queue model that can not reproduce the memory effects or the activity-dependent distributions. We think there is another kind of human activity patterns driven by personal interests and characterized by strong memory effects. Accordingly, we propose a simple model based on temporal preference, which can well reproduce both the heavy-tailed nature and the strong memory effects. This work helps in understanding both the temporal regularities and the predictability of human behaviors.

physics.soc-ph↗

arXiv2010

Bridgeness: A Local Index on Edge Significance in Maintaining Global Connectivity

Edges in a network can be divided into two kinds according to their different roles: some enhance the locality like the ones inside a cluster while others contribute to the global connectivity like the ones connecting two clusters. A recent study by Onnela et al uncovered the weak ties effects in mobile communication. In this article, we provide complementary results on document networks, that is, the edges connecting less similar nodes in content are more significant in maintaining the global connectivity. We propose an index named bridgeness to quantify the edge significance in maintaining connectivity, which only depends on local information of network topology. We compare the bridgeness with content similarity and some other structural indices according to an edge percolation process. Experimental results on document networks show that the bridgeness outperforms content similarity in characterizing the edge significance. Furthermore, extensive numerical results on disparate networks indicate that the bridgeness is also better than some well-known indices on edge significance, including the Jaccard coefficient, degree product and betweenness centrality.

physics.soc-ph↗

arXiv2010

Link Prediction in Complex Networks: A Survey

Link prediction in complex networks has attracted increasing attention from both physical and computer science communities. The algorithms can be used to extract missing information, identify spurious interactions, evaluate network evolving mechanisms, and so on. This article summaries recent progress about link prediction algorithms, emphasizing on the contributions from physical perspectives and approaches, such as the random-walk-based methods and the maximum likelihood methods. We also introduce three typical applications: reconstruction of networks, evaluation of network evolving mechanism and classification of partially labelled networks. Finally, we introduce some applications and outline future challenges of link prediction algorithms.

physics.soc-ph↗

arXiv2010

Bilinear effect in complex systems

The distribution of the lifetime of Chinese dynasties (as well as that of the British Isles and Japan) in a linear Zipf plot is found to consist of two straight lines intersecting at a transition point. This two-section piecewise-linear distribution is different from the power law or the stretched exponent distribution, and is called the Bilinear Effect for short. With assumptions mimicking the organization of ancient Chinese regimes, a 3-layer network model is constructed. Numerical results of this model show the bilinear effect, providing a plausible explanation of the historical data. Bilinear effect in two other social systems is presented, indicating that such a piecewise-linear effect is widespread in social systems.

physics.soc-ph↗

arXiv2010

Domain Walls in Normal and Superconducting States of Iron Pnictides

The electronic and magnetic structures in the normal and superconducting states of iron pnictides are investigated by solving self-consistently the Bogoliubov-de Gennes equation. It is shown that strong electron correlations can induce domain walls, which separate regions with different spin density wave orders. At zero or low electron doping, $90^\circ$ domain walls are formed while anti-phase domain walls are produced at higher electron doping. On the domain walls, larger electron densities are always present. The results agree qualitatively with recent observations of scanning tunneling microscopy and superconducting quantum interference device microscopy.

cond-mat.supr-con↗