基于PageRank的网络社区意见领袖发现算法

意见领袖是网络社区中积极的信息传播者和信息引导者,对其影响力的评估是社交网络分析的一项重要内容。针对现有算法对用户动态行为分析和动态内容影响考虑欠缺而不能客观反映真实情况的问题,提出一种基于用户影响力和PageRank的意见领袖发现算法,综合考虑用户自身影响力、用户动态行为影响度和用户行为给动态内容带来的真实影响。通过从知乎网络社区收集的大规模数据实验结果表明,该算法更具合理性并能有效地提高网络社区意见领袖的识别准确度。     

结合用户生成内容与链接关系的社区发现算法

社区发现一直是社会网络研究中的热点内容。但是当前社区发现算法更加关注用户与用户之间的链接关系,而对社会网络中用户生成内容(user generated contents,UGC)大数据研究较少。用户生成内容是Web2.0的特点,也是社会网络平台吸引用户的重要原因之一,对社区的形成起着重要作用。提出了一种新的社区发现算法,能够综合利用用户与用户之间的链接关系以及用户生成内容来确定用户的社区划分。该算法用LDA(latent Dirichlet allocation)算法分析用户生成内容中主要的内容形式——文本信息,同时通过谱分析方法分析用户与用户之间的链接关系,并有机结合以发现网络的社区结构。通过分析科学网的真实数据,证明了所提算法能够有效综合利用用户生成内容与用户链接关系,使社区发现的结果更加客观准确。     

基于LDA的新闻话题子话题划分方法

针对目前网络热点新闻话题中存在的难以区分一个话题下的多个子话题现象,提出一种基于LDA模型的子话题划分方法.首先应用LDA模型对新闻文档进行建模,采用贝叶斯标准方法确定最优主题个数,使LDA模型拟合文档性能达到最佳;其次针对子话题间文本相似度较高的特点,引入主题特征词相关性分析,采用改进的KL距离公式,计算新闻文档之间相似度,有效区分了文档内容相似但话题重点不同的报道;最后通过single-pass增量聚类算法进行文档聚类,实现子话题划分.实验验证了改进后的相似度计算方法的有效性,实验结果表明该方法能够有效地提高热点新闻话题子话题划分的准确率.     

基于LDA模型的社交网络主题社区挖掘

以微博为代表的社交网络已成为社会舆情的战略要地。对于社交网络中隐含主题社区的发掘,具有较高的商业推广和舆情监控价值。近年来,概率生成主题模型LDA(Latent Dirichlet Allocation)在数据挖掘领域得到了广泛应用。但是,一般而言,LDA适用于处理文本、数字信号数据,并不能合理地用来处理社交网络用户的关系数据。对LDA进行修改,提出适用于处理用户关系数据的Tri-LDA模型,挖掘社交网络中的主题社区。实验结果表明,基于Tri-LDA模型,进行机器学习所得到的结果基本能够反映社交网络上真实的主题社区分布情况。     

基于信任度的并行化社区发现算法

现有的社交网络快速划分社区算法存在质量低、不能充分利用节点链接信息的问题,而效果较好的划分算法也存在时间复杂度高、无法应用于大规模社交网络的问题。为此,提出一种基于MapReduce的社区发现算法。利用PGP算法内信任者推荐模型迭代计算用户之间的信任强度,通过社区传播的方式聚合节点。在经典数据集上和大规模新浪微博数据集上进行实验,结果表明,该算法能有效度量用户间的信任度,得到准确的社区发现结果。     

基于领域的影响力最大化与病毒营销

近年来随着新浪微博、人人网等社交网络新媒体的涌现,线上影响力传播得到了越来越多企业和研究机构的关注。如何在给定资源的约束下实现最大的传播范围(影响力最大化问题),对病毒营销等市场战略的有效开展有着重要意义。如果能充分利用社交网络上的异质性信息来更准确地定位用户所属的领域,进而基于领域实现影响力最大化,将对从整体角度出发的传统研究和片面的结构或内容角度的研究形成很好的补充。该文同时利用新浪微博上用户之间的社交关系和微博内容的话题两个维度的信息将用户划分为不同的领域;进而提出了一种基于贪心和动态规划混合的改良算法实现基于领域的影响力最大化。实验表明该文的领域影响力模型较好优化了传统影响力最大化的时间消耗,同时拥有相近的精度。     

基于SRank的社交网络影响力分析

针对社交网络中用户影响力的评价问题,提出了一种基于SRank的评价算法。基于从社交网络中收集的大规模数据集,结合最近社会学理论研究成果分析PageRank及其改进算法应用于此场景中的不足。在此基础上总结社交网络中信息传播的规律,将用户与社交网络的关系强度定义为用户的人缘值,用来表示用户作为粉丝的信息再传播能力。然后提出了一个通过预测用户信息传播能力大小来分析和度量用户影响力的SRank用户影响力模型。在同样的数据集下相对于PageRank及其改进算法,SRank用户影响力模型获得了更好的影响力预测结果。基于大规模数据的实验结果表明,提出的方法是较为有效的。     

面向微博影响力的社交网络特征分析

社交网络的影响力与其自身的结构特征密切相关。基于新浪微博的数据,对用户的粉丝数、关注数的分布及这些特征之间的关系进行分析,发现用户的粉丝数、关注数、微博数都符合幂律分布;探讨了节点之间的距离特征,发现并证明了微博网络中存在着“小世界”现象;研究了节点之间的链接形成问题,发现链接的形成满足三元闭包原理。以上三方面研究结果,对于探索微博影响力同底层社交网络结构特征的关系、设计微博影响力控制机制具有重要的意义。     

基于 LDA 模型的 Ad hoc 信息检索方法研究

传统的话题模型假设每个文档只属于一个话题,而实际情况下一个文档往往与多个话题相关。应用LDA 模型将文档表示为多个话题的组合,并基于语言模型框架,提出了一种基于 LDA 的混合模型用于文本信息的 Ad hoc 检索。该方法将 LDA 模型与文档模型相结合,与聚类模型相比,在保持较低的计算复杂度外,具有很高的检索性能,因此更适用于大规模文档集的信息检索。     

社交网络中用户隐私推理与保护研究综述

如今微博和Twitter等社交网络平台被广泛地用于交流、创建在线社区并进行社交活动。用户所发布的内容可以被推理出大量隐私信息,这导致社交网络中针对用户的隐私推理技术的兴起。利用用户的文本内容及在线行为等知识可以对用户进行推理攻击,社交关系推理和属性推理是对社交网络用户隐私的两种基本攻击。针对推理攻击保护机制和方法的研究也在日益增加,对隐私推理和保护技术相关的研究和文献进行了分类并总结,最后进行了探讨和展望。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.