兴趣社交网络中的供需匹配研究:以豆瓣网为例

近年来兴起的兴趣社交网络中因其内在的商业价值引起了人们的注意.兴趣社交网络中涌现出大量的商品供需信息,带来的问题之一就是商品供需信息传播匹配效率低下.为解决上述问题,本文依托社会网络分析方法,探讨在具备小世界特性的兴趣社交网络中商品供需匹配的特点,研究商品传播和匹配的规律和提高匹配效率的策略.本文选取豆瓣网关注关系为实证数据,提出在兴趣社交网络中友邻信息相关度与供需信息传播匹配效率正相关的假设,并采用计算机仿真方法来验证假设.论文获取豆瓣网的社交网络数据、包括网络用户藏书数据和图书的标签数据,针对随机选取的1000个用户和200本图书作为实验样本,分别设计两套友邻信息相关度度量算法和两套兴趣社交网络中商品供需信息传播匹配算法,采用进行仿真模拟实验进行了比较.实验结果证实了人们对于商品检索的直观判断,得出在兴趣社交网络中,商品供需信息传播匹配效率与友邻信息相关度正相关的结论.     

On predictive distributions and Bayesian networks

In this paper we are interested in discrete prediction problems for a decision-theoretic setting, where the task is to compute the predictive distribution for a finite set of possible alternatives. This question is first addressed in a general Bayesian framework, where we consider a set of probability distributions defined by some parametric model class. Given a prior distribution on the model parameters and a set of sample data, one possible approach for determining a predictive distribution is to fix the parameters to the instantiation with the maximum a posteriori probability. A more accurate predictive distribution can be obtained by computing the evidence (marginal likelihood), i.e., the integral over all the individual parameter instantiations. As an alternative to these two approaches, we demonstrate how to use Rissanen's new definition of stochastic complexity for determining predictive distributions, and show how the evidence predictive distribution with Jeffrey's prior approaches the new stochastic complexity predictive distribution in the limit with increasing amount of sample data. To compare the alternative approaches in practice, each of the predictive distributions discussed is instantiated in the Bayesian network model family case. In particular, to determine Jeffrey's prior for this model family, we show how to compute the (expected) Fisher information matrix for a fixed but arbitrary Bayesian network structure. In the empirical part of the paper the predictive distributions are compared by using the simple tree-structured Naive Bayes model, which is used in the experiments for computational reasons. The experimentation with several public domain classification datasets suggest that the evidence approach produces the most accurate predictions in the log-score sense. The evidence-based methods are also quite robust in the sense that they predict surprisingly well even when only a small fraction of the full training set is used.     

Machine learning and design of experiments with an application to product innovation in the chemical industry

Industrial statistics plays a major role in the areas of both quality management and innovation. However, existing methodologies must be integrated with the latest tools from the field of Artificial Intelligence. To this end, a background on the joint application of Design of Experiments (DOE) and Machine Learning (ML) methodologies in industrial settings is presented here, along with a case study from the chemical industry. A DOE study is used to collect data, and two ML models are applied to predict responses which performance show an advantage over the traditional modeling approach. Emphasis is placed on causal investigation and quantification of prediction uncertainty, as these are crucial for an assessment of the goodness and robustness of the models developed. Within the scope of the case study, the models learned can be implemented in a semi-automatic system that can assist practitioners who are inexperienced in data analysis in the process of new product development.     

基于自组网技术的燃气无线抄表系统研究

为解决现阶段燃气无线抄表系统数据采集中无线网络不稳定、路由协议复杂、自修复能力薄弱等问题，提出并设计了一种基于cc1101无线传送模块的树形拓扑结构无线自组网系统。系统中主要对数据采集层路由协议和硬件实现进行了研究和设计，分析了该燃气无线抄表系统与传统燃气无线抄表系统的不同之处，设计了该系统数据采集层网络传输协议和总体结构。无线节点建在穿透力强的433 MHz的频率下进行通信，保证了系统自组网的稳定快速。     

Social Networks Derived from Affiliations and Friendships, Multi-informant and Self-reports: Stability, Concordance, Placement of Aggressive and Unpopular Children, and Centrality

This study compares three variations in how researchers construct middle childhood social networks: (1) with friendships or affiliations as a relational tie; (2) with children providing self reports of relationships, or in addition, multi-informant reports of relationships in which they are not involved; and (3) whether network computation is correlational or distance-based . The sample was 357 fourth- and fifth-grade students in 17 classrooms. The strongest differences were between self-reported friendship and affiliative networks. Results showed that compared with affiliations, friendship networks had smaller groups, more isolates, and lower fall-to-spring stability. Agreement in social placement between friendship and affiliative networks was generally average, but poor for unpopular and aggressive children. Multi-informant affiliative networks were most robust in their positioning of aggressive children. Multi-informant centrality was uniquely uncorrelated with aggression. Network computation differences were not substantial. Discussion focuses on recommendations for research and the educational promise of network technology.     

制度与非制度因素对农民工落户城镇意愿的影响

农民工能否落户城镇对我国的新型城镇化建设有重大的现实影响。利用2013年全国流动人口动态监测数据,从制度性因素和非制度性因素两方面对农民工的落户城镇意愿进行了探讨。实证研究发现：社会保险状况及学龄子女是否在本地就学会显著影响农民工的落户意愿,表明制度性因素的重要;从社会网络视角来看,基于传统的先赋性场域网络如亲属网对农民工的落户意愿无显著影响,而基于现代社会的自致性场域网络如朋友网、行政组织网、工作同事网则显著提高了农民工落户城镇的意愿。     

基于共引网络理论的产业需求竞争网络

根据2002-2012年北京市投入产出的直接消耗系数,结合共引网络的建模思想,构建一类加权无向网络——产业需求竞争网络,并引入边权、单位权和差异性作为衡量网络中竞争关系的指标。通过研究发现:INCN-BJ网络的边权反映了产业链环节的完善程度,单位权反映了产品部门对产业系统的促进作用,差异性则区分出产业系统中需要加大产业政策指导的落后产品部门。     

The potential of online social networking data for augmenting the study of high-risk personal networks among young men who have sex with men at-risk for HIV

Capturing dynamics in high-risk personal networks is essential for preventing HIV transmission. Online social networking data offer incentive to augment traditional selfreported approaches for network enumeration. To explore what online networks reveal about dynamics among high-risk associates, we examine the relationship between egocentric confidant and sex networks and personal Facebook friendship networks of a cohort of young Black men who have sex with men. Although overlap exists between self-reported and Facebook associates, the stabilities of each were unrelated. Confidants who were also Facebook friends with a respondent were, however, more likely to be retained. Thus, Facebook networks contain stable confidants.     

k-means-based algorithm for blockmodeling linked networks

The paper presents a k-means-based algorithm for blockmodeling linked networks where linked networks are defined as a collection of one-mode and two-mode networks in which units from different one-mode networks are connected through two-mode networks. The reason for this is that a faster algorithm is needed for blockmodeling linked networks that can better scale to larger networks. Examples of linked networks include multilevel networks, dynamic networks, dynamic multilevel networks, and meta-networks. Generalized blockmodeling has been developed for linked/multilevel networks, yet the generalized blockmodeling approach is too slow for analyzing larger networks. Therefore, the flexibility of generalized blockmodeling is sacrificed for the speed of k-means-based approaches, thus allowing the analysis of larger networks. The presented algorithm is based on the two-mode k-means (or KL-means) algorithm for two-mode networks or matrices. As a side product, an algorithm for one-mode blockmodeling of one-mode networks is presented. The algorithm’s use on a dynamic multilevel network with more than 400 units is presented. A situation study is also conducted which shows that k-means based algorithms are superior to relocation algorithm-based methods for larger networks (e.g. larger than 800 units) and never much worse.     

基于行动者网络理论的三网融合发展战略研究

行动者网络理论为三网融合的发展提供了一种新视角和新的分析工具。研究表明:三网融合既是技术创新和市场竞争推动的结果,也是政府管制的结果;作为核心行动者,政府应采取合理的手段调整行动主体的行为,引导其积极加入到网络中;在多异质行动者参与的三网融合博弈进程,由于诸多利益因素的存在,网络有可能重构,甚至瓦解。我国应从制定合理的发展路径和科学的实施步骤、完善政策资源供给和重视各方利益整合等方面加强三网融合发展战略指导。