Application of collective knowledge diffusion in a social network environment

ABSTRACT

We present a group dynamics model that shows knowledge integration as a process occurring over time. As each individual in the group contact others, his own knowledge changes, and over time the collective knowledge is obtained. This allows modeling knowledge diffusion in a social network and while the models presented in this paper are not competitive in that area, they approach the problem from previously unconsidered direction. We test the behavior of the model in a multi-agent simulation and we test a simple advertisement campaign in a social network. We provide discussion of elements needed for making model more competitive.     

Market microstructure in a global B2B network

On‐line marketplaces raise several interesting issues, among them the relevance of location when content is digitized, and the assessment of a supplier's capabilities when buyers worldwide only have electronic contact with sellers. In global B2B on‐line marketplaces, market microstructures, i.e. which firms compete for the same customers, are thus likely to be influenced by how customers value location and firm capabilities in their decisions to do business with different suppliers on‐line. We suggest that both these sets of attributes will continue to matter on‐line—firms possessing similar capabilities, as well as firms that are similar in location by country, time zones or clusters, will compete for business from the same customers. We model the similarity in competitive positions between pairs of firms based on the overlap in their customer networks, using data on actual interactions between supplier and customer banks on an electronic trading system. Using QAP network regression techniques on the 100 largest banks in this industry, we find that similarity in capabilities influences who competes with whom, and that location still matters in a global B2B exchange. Interestingly, location influences who a firm's competitors are, but not where its customers are from. Copyright © 2001 John Wiley & Sons, Ltd.     

The European high-speed train network: Predicted effects on accessibility patterns

The principal aim of this paper is to evaluate the impact of the future European high-speed train network on accessibility, by reducing time distance between places and modifying their relative location. We compare the current situation with that foreseen for the year 2010, according to the Outline Plan of the European High-Speed Train Network, in order to analyse which areas will most benefit from construction and improvement of the infrastructure. It is hypothesized that the high-speed train will certainly bring the peripheral regions closer to the central ones, but will also increase imbalances between the main cities and their hinterlands. A weighted average distance indicator is applied for this purpose. This measure identifies the spatial distribution of accessibility in the area of study, emphasizing the infrastructure effects, and locates accessibility changes at the European level. A Geographic Information System (GIS) has been used to carry out this study.     

Predicting the geo-temporal variations of crime and disorder

Traditional police boundaries—precincts, patrol districts, etc.—often fail to reflect the true distribution of criminal activity and thus do little to assist in the optimal allocation of police resources. This paper introduces methods for crime incident forecasting by focusing upon geographical areas of concern that transcend traditional policing boundaries. The computerised procedure utilises a geographical crime incidence-scanning algorithm to identify clusters with relatively high levels of crime (hot spots). These clusters provide sufficient data for training artificial neural networks (ANNs) capable of modelling trends within them. The approach to ANN specification and estimation is enhanced by application of a novel and noteworthy approach, the Gamma test (GT).     

信息服务模式及网络利用

当今的用户获取信息的渠道越来越广,这使得信息服务面临着多方面的竞争。对于从事信息服务的工作者而言,如何让信息真正有效地服务于各行各业和广大用户,以及依据什么因素来选择恰当的服务模式与推动模式的更新都是非常重要的。文章初步探讨了信息服务模式的变化,以及网络在信息服务中的利用。     

Bayesian MCMC Mapping of Quantitative Trait Loci in a Half-sib Design: a Graphical Model Perspective

Graphical models provide a powerful and flexible approach to the analysis of complex problems in genetics. While task-specific software may be extremely efficient for any particular analysis, it is often difficult to adapt to new computational challenges. By viewing these genetic applications in a more general framework, many problems can be handled by essentially the same software. This is advantageous in an area where fast methodological development is essential. Once a method has been fully developed and tested, problem-specific software may then be required. The aim of this paper is to illustrate the potential use of a graphical model approach to genetic analyses by taking a very simple and well-understood problem by way of example.     

Codes of Conduct in Subcontracting Networks: A Labour Law Perspective

In the past ten years, many European companies organised into subcontracting networks have decided to adopt codes of conduct to regulate labour relations and to ensure the respect of fundamental social rights. This paper first determines the context and the issues to be addressed by codes of conduct within networks of companies, and second analyses the terms under which they can be implemented. The paper argues that codes of conduct can complement the standards developed by States, the European Union or the social partners, but that steps should be taken in order to avoid that these texts replace the existing labour law.     

网络时代中间商发展趋势及特点浅谈

阐述了中间商、新中间商的概念,归纳、分析了中间商在网络时代下存在的必要性、可能性及其发展的新特点和可能趋势。     

基于递归对角神经网络自适应均衡算法的研究

阐述了神经网络自适应均衡算法的基本原理,提出了一种基于递归对角神经网络的自适应均衡算法,推导了算法的迭代公式,进行了计算机仿真。结果表明,随着传输信号信噪比的增加,稳态剩余误差减小,误码率降低。     

人工神经网络在住房销售率预测中的应用

住房销售率是开发商最为关心的问题之一。多种不确定因素的影响为准确的预测销售率带来困难。人工神经网络能够模拟人脑的思维过程,建立多个变量的非线性模型,从而为准确预测住房销售率提供了一种新思路。