We investigate the dynamics of random walks on weighted networks. Assuming that the edge weight and the node strength are used as local information by a random walker. Two kinds of walks, weight-dependent walk and str...We investigate the dynamics of random walks on weighted networks. Assuming that the edge weight and the node strength are used as local information by a random walker. Two kinds of walks, weight-dependent walk and strength-dependent walk, are studied. Exact expressions for stationary distribution and average return time are derived and confirmed by computer simulations. The distribution of average return time and the mean-square displacement are calculated for two walks on the Barrat-Barthelemy-Vespignani （BBV） networks. It is found that a weight-dependent walker can arrive at a new territory more easily than a strength-dependent one.展开更多
The economy of a country can be modeled as a complex system in which several players buy and sell goods from each other.By analyzing the investment flows,it is possible to reconstruct the supply chain for the producti...The economy of a country can be modeled as a complex system in which several players buy and sell goods from each other.By analyzing the investment flows,it is possible to reconstruct the supply chain for the production of most goods,whose understanding is important to analysts and public officials interested in creating and evaluating strategies for informed and strategic decision making,for instance,adjusting tax policies.Those networks of players and investments,however,tend to be complex and very dense,which leads to over-plotted visualizations that obfuscate precious information such as the dependencies between productive sectors and regions.In this paper,we propose Hermes,a guidanceenriched Visual Analytics environment(named after the Greek God of Commerce)for the exploration of complex economic networks,to uncover supply chains,regions’productivity,and sector-to-sector relationships.With practical knowledge regarding guidance,we designed and implemented a visual sub-graph querying approach to extract patterns from such complex investment graphs obtained from real-world data.We present a three-fold evaluation of the system:we perform a qualitative evaluation of our approach with three domain experts,a separate assessment of the proposed guidance features with an expert researcher in this field,and a case study of Hermes using a bank account network dataset to demonstrate the generalizability of our approach.展开更多
文摘We investigate the dynamics of random walks on weighted networks. Assuming that the edge weight and the node strength are used as local information by a random walker. Two kinds of walks, weight-dependent walk and strength-dependent walk, are studied. Exact expressions for stationary distribution and average return time are derived and confirmed by computer simulations. The distribution of average return time and the mean-square displacement are calculated for two walks on the Barrat-Barthelemy-Vespignani （BBV） networks. It is found that a weight-dependent walker can arrive at a new territory more easily than a strength-dependent one.
基金This work was partially supported by the Research Cluster"Smart Communities and Technologies(SmartCT)"at TU Wien and the Austrian Science Fund(FWF),grant P31419-N31 Knowledge-Assisted Visual Analytics(KnoVA).
文摘The economy of a country can be modeled as a complex system in which several players buy and sell goods from each other.By analyzing the investment flows,it is possible to reconstruct the supply chain for the production of most goods,whose understanding is important to analysts and public officials interested in creating and evaluating strategies for informed and strategic decision making,for instance,adjusting tax policies.Those networks of players and investments,however,tend to be complex and very dense,which leads to over-plotted visualizations that obfuscate precious information such as the dependencies between productive sectors and regions.In this paper,we propose Hermes,a guidanceenriched Visual Analytics environment(named after the Greek God of Commerce)for the exploration of complex economic networks,to uncover supply chains,regions’productivity,and sector-to-sector relationships.With practical knowledge regarding guidance,we designed and implemented a visual sub-graph querying approach to extract patterns from such complex investment graphs obtained from real-world data.We present a three-fold evaluation of the system:we perform a qualitative evaluation of our approach with three domain experts,a separate assessment of the proposed guidance features with an expert researcher in this field,and a case study of Hermes using a bank account network dataset to demonstrate the generalizability of our approach.
