The use of sparsest cuts to reveal the hierarchical community structure of social networks

We show that good community structures can be obtained by partitioning a social network in a succession of divisive sparsest cuts. A network flow algorithm based on fundamental principles of graph theory is introduced to identify the sparsest cuts and an underlying hierarchical community structure of the network via maximum concurrent flow. Matula [Matula, David W., 1985. Concurrent flow and concurrent connectivity in graphs. In: Alavi, Y., et al. (Eds.), Graph Theory and its Applications to Algorithms and Computer Science. Wiley, New York, NY, pp. 543–559.] established the maximum concurrent flow problem (MCFP), and papers on divisive vs. agglomerative average-linkage hierarchical clustering [e.g., Matula, David W., 1983. Cluster validity by concurrent chaining. In: Felsenstein, J. (Ed.), Numerical Taxonomy: Proc. of the NATO Adv. Study Inst., vol. 1. Springer-Verlag, New York, pp. 156–166 (Proceedings of NATO ASI Series G); Matula, David W., 1986. Divisive vs. agglomerative average linkage hierarchical clustering. In: Gaul, W., and Schader, M. (Eds.), Classification as a Tool of Research. Elsevier, North-Holland, Amsterdam, pp. 289–301; Thompson, Byron J., 1985. A flow rerouting algorithm for the maximum concurrent flow problem with variable capacities and demands, and its application to cluster analysis. Master Thesis. School of Engineering and Applied Science, Southern Methodist University] provide the basis for partitioning a social network by way of sparsest cuts and/or maximum concurrent flow.     

Approximations for Gibbs Distribution Normalising Constants

A key difficulty in the use of Gibbs prior distributions in Bayesian image analysis is the intractability of the normalisation constant. One approach is to perform off-line simulations which allow a calibration of normalisation constant against prior parameter. In this paper the reverse-logistic regression approach to calibration will be examined for various Gibbs distributions and explicit parametric equations will be proposed. A simple method for combining separate calibrations will be illustrated and the relationship between normalisation constant and image size will be explored with an empirical approximation proposed.     

Survey sampling in graphs

The Horvitz-Thompson estimation theory is applied to snowball sampling and some other sampling procedures using a known or unknown graph structure in the survey population. In particular, simple graph-parameter estimators and variance estimators are obtained which are based on various kinds of partial information about the graph.     

三元劳动力市场分割与“新失业群体”失业——基于辽宁的调查

本文主要从辽宁省基本社会特质入手,从制度的角度展开“新失业群体”存在的根源分析。主要是从东北老工业基地特有的三元劳动力市场分割的视角来分析“新失业群体”何以在辽宁省特别突出。即由于劳动力市场三元分割,使得“新失业群体”在不同劳动力市场之间的职业流动发生障碍,导致了“新失业群体”的失业。     

采用网络分割的OBS网络故障监测机制

提出了一种基于网络分割策略的圈覆盖光突发交换网络的故障监测机制,采用网络分割策略,大型的光突发交换网络被分割成便于故障管理的带有中心节点的环形子网或扇形子网,在每个子网内分别执行圈覆盖算法进行故障监测。计算和统计结果表明,该故障监测机制对于节点平均连通度大于3的网络具备网络开销小、故障定位率低等特点。     

盐城市行政区划单位名的词汇学研究

盐城市区划名是盐城市地名中有代表性的重要类别。从词汇单位、词汇类聚、词形类聚、词义类聚、词的结构等方面着重研究盐城市区划名中的专名,可见其词汇学要素分布呈不均衡状态且因区划名命名的不断规范化而有日益加剧的趋势。     

新城市引力模型下辽宁省城市圈的划分

新城市引力模型引入城市职能参数,人口修正参数和经济距离修正参数,改进原来简单的城市引力模型,深入探讨城市职能对城市引力的影响。并运用新城市引力模型对辽宁省14个城市进行数据分析,并以沈阳与大连两个优势城市为中心计算城市引力。最终对辽宁省14个城市进行城市圈进行了划分,形成以沈阳为中心,大连为次中心的城市圈布局。     

Dense core model for cohesive subgraph discovery

Discovery of cohesive subgraphs is an important issue in social network analysis. As representative cohesive subgraphs, pseudo cliques have been developed by relaxing the perfection of cliques. By enumerating pseudo clique subgraphs, we can find some structures of interest such as a star-like structure. However, a little more complicated structures such as a core/periphery structure is still hard to be found by them. Therefore, we propose a novel pseudo clique called ρ-dense core and show the connection with the other pseudo cliques. Moreover, we show that a set of ρ-dense core subgraphs gives an optimal solution in a graph partitioning problem. Several experiments on real-life networks demonstrated the effectiveness for cohesive subgraph discovery.     

GOODNESS OF FIT FOR THE BINOMIAL DISTRIBUTION

Goodness of fit testing for the binomial distribution can be carried out using Pearson's X²_p statistic and its components. Applications of this technique are considered and compared with recently suggested empirical distribution function tests. Diagnostic use of components is discussed.     

三火球模型中参数配分温度的计算

利用夸克-胶子等离子体模型的计算结果计算三火球模型中的参数配分温度,计算值和实验结果符合。