基于梯度提升决策树的微博虚假消息检测

微博是信息共享的重要平台,同时,也成为虚假消息产生和推广的重要平台,虚假消息的传播严重扰乱了社会秩序。为了快速、有效地识别微博虚假消息,提出一种基于梯度提升决策树（GBDT）的虚假消息检测方法。首先,从评论的角度分析微博虚假消息和真实消息之间存在的差异,在此基础上提取评论中的文本内容、用户属性,信息传播和时间特性的分类特征;然后,基于分类特征,采用GBDT算法实现微博虚假消息识别模型;最后,在两个真实的微博数据集上进行验证。实验结果表明,基于GBDT的识别模型能有效提高微博虚假消息检测的准确率。     

基于DCA算法的微博虚假信息检测

通过对微博虚假信息的分析,基于DCA算法的思想,提出一种检测微博虚假信息的方法。以新浪微博为例,从虚假信息发布者的用户属性和虚假信息评论的文本内容两个方面进行分析。从用户方面选取用户的特征属性,如是否认证、有无简介、地址信息是否详细、关注数、粉丝数等,从评论内容方面选取评论与微博内容的相关性、评论的支持性及其置信度等特征属性,将以上属性的分析结果作为区别虚假信息与真实信息的特征信号,并基于树突状细胞算法（Dendritic Cells Algorithm, DCA）实现新浪微博虚假信息的识别。使用新浪微博真实数据对算法有效性进行了验证和对比实验,结果表明该方法能够有效检测出新浪微博中的虚假信息,具有较高的检测准确率。     

基于虚假评论识别的微博评论情感分析的研究与应用

微博作为时下热门的社交网络平台,针对其所产生的评论文本进行情感分析已经成为人工智能领域的一个研究热点。考虑到虚假评论会降低情感分析的准确度,从评论用户的状态和行为出发,提出一种基于用户状态与行为的可信度评价体系,用于提取虚假评论特征。结合该特征与PU(Positive and unlabeled)学习算法进行虚假评论识别;运用SVM分类器和随机梯度下降回归模型对去除虚假评论的文本进行主观句分类与情感分析。实验表明,进行虚假评论识别后的情感分析准确率、召回率分别达到0.88和0.89,比传统方法具有更高的分析效能。     

结合信任和用户关系的微博关注推荐算法*

用户关注推荐在微博信息分享平台中扮演着非常重要的角色,现有的用户关注推荐模式多采取内容及背景相似性度量用户距离,且多数使用单一因素进行排序推荐,没有针对用户群体进行分类,推荐效果一般。因此提出了一种针对非名人用户的新型关注推荐算法RTLR,该算法同时使用用户关系和互动行为信息进行推荐,并结合多因素建立逻辑回归模型。从国内用户最多的新浪微博中采集真实数据进行实验,结果显示新型模型有效的提高了关注推荐的准确性。     

微博信息传播的“自澄清”机制分析

通过对微博信息传播过程中产生的虚假信息及虚假信息的自动澄清机制进行分析,探讨微博谣言"自澄清"机制的形成条件、形成过程,以及该机制对微博发展的作用。探究如何更好地利用微博信息传播的"自澄清"机制,帮助用户正确地使用微博,促进微博的健康发展。     

基于图排序模型的微博观点信息识别

随着在线社交网络的爆炸式增长,微博已成为人们发表观点和表达情绪的重要平台。微博不仅可以反映用户的观点,还可以通过转发方式等传递观点,进而影响其他用户的观点。然而,微博以其简短、口语化等特点,给识别观点带来了新的挑战。仅仅基于文本进行观点分析的传统方法在分析微博观点倾向时,效果并不理想。为解决此问题,提出了一种基于图排序模型的微博观点信息识别算法。首先,利用布尔模型表示微博文本,并用逻辑回归进行观点分析获得伪标签;然后,利用上下文关系构建微博关系图,并利用受限玻尔兹曼机抽取高维特征;最后,基于图排序模型识别微博观点信息。实验结果表明,该算法能有效地对微博观点进行识别。     

基于行为分析的微博信息传播效果

微博的传播效果研究对于提高市场营销效率、加强舆情监控和准确发现热点具有重要作用。针对以前传播效果研究中未考虑用户个体差异的问题,提出一种基于行为分析的微博转发规模和传播深度预测方法。从微博用户自身、用户关系和微博内容3个方面提取9个相关特征,结合逻辑回归（LR）方法提出一种转发行为预测模型,并基于此模型结合信息沿用户传播特点,通过逐级对相邻用户迭代统计分析得到转发规模和传播深度预测方法。在新浪微博数据集上的实验结果表明,所提方法对转发规模和传播深度预测的正确率分别约为87.1%和81.6%,能较好地预测出信息传播效果。     

手机广告智能分发和精细化营销模型

本文主要分析了移动通信时代下企业和用户的信息服务需求,提出了一种手机广告智能分发和精确投放的模型,采用3+N用户属性理论对用户电信数据进行分析和分类,利用逻辑表达式进行广告需求人群和用户模型的智能匹配,并采用逻辑回归模型对用户属性数据进行了精确构建,并对方案进行分析.     

基于网络拓扑结构视角的社交媒体用户转发预测算法

为预测某条微博的具体转发者,在微博是否会被转发的研究基础上,提出了基于社交网络拓扑结构、用户行为及用户间关联三个层面的逻辑回归分类算法,并针对该算法进行真实数据集检测。实验结果表明该预测算法与未考虑网络拓扑结构的算法相比性能显著提升,为实现社交媒体信息传播轨迹精准预测打下重要基础。     

基于逻辑回归算法的微博水军识别

受潜在的商业利益的驱动,微博水军横行于话题与评论之间,对人们了解真实的结果产生不良影响,成为正常用户了解事实真相的障碍。分析了正常用户和水军的关系图,以此为切入点,分析了水军的特点,从用户属性中抽取了8个特征数据(粉丝数、关注数、好友粉丝比、注册时间、活跃度、关注速率、双向关注比和互粉数)基于学习数据集R训练逻辑回归分类模型,得到可靠的回归系数后,使用识别样本集R进行识别,水军识别率高达98.770%。为验证抽取的8个特征是否能有效识别水军,使用Scikit-Learn机器学习库中4种分类方法对同一识别样本集进行水军识别,水军识别准确率均在98.688%以上。研究结果表明,选取的8个特征能有效地进行水军判别,逻辑回归分类模型在进行水军识别研究中具有高准确性和可靠性。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.     

The Distributed Time-Triggered Simulation Scheme: Core Principles and Supporting Execution Engine

Distributed real-time simulation is a young technology field but its practice is under increasing demands. In recent years the author and his collaborators have been establishing a new approach called the distributed time-triggered simulation (DTS) scheme which is conceptually simple and easy to use but widely applicable. The concept was initiated in the course of developing a new-generation object-oriented real-time programming scheme called the time-triggered message-triggered object (TMO) programming scheme. Some fundamental issues inherent in distributed real-time simulation that were learned during recent experimental studies are discussed along with some approaches for resolving the issues. An execution engine developed to support both the TMOs engaged in control computation and the TMOs engaged in DTS is also discussed along with its possible extensions that will enable significantly larger-scale DTSs.     

Software-Konfigurationsmanagement in großen Softwareprojekten

Zusammenfassung Mit zunehmender Größe der Softwaresysteme verschärfen sich die für die Software-Herstellung typischen Probleme: Beherrschen großer Objektmengen, Erhalten der Systemkonsistenz, Kontrolle der ständigen Änderungseinflüsse und Gewährleisten einer langen Lebensdauer. Die Disziplin Konfigurationsmanagement bildet den methodischen Ansatz, diese Probleme besser zu beherrschen. Software-Konfigurationsmanagement faßt die Herstellung von Softwaresystemen als eine Abfolge von kontrollierten Änderungen an gesicherten Zwischen- und Endergebnissen auf. Dargestellt werden die Objekte und Funktionen des Software-Konfigurationsmanagements sowie die hierfür in großen Software-Projekten benötigten Methoden, Instanzen und Hilfsmittel.     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and     

Editorial:Brain-machine interface(BMI) and cyborg intelligence

正Brain-machine interfaces(BMIs)aim at building a direct communication pathway between the brain and an external device,and represent an area of research where significant progress has been made during the past decade.Based on BMIs,mind information can be read out by neural signals to control     

Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate     

SCIENCE CHINA Information Sciences SUBJECT INDEX TO VOLUME 57(2014)

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Information for Authors

正http://www.zju.edu.cn/jzus http://www.springerlink.com Aim The Journals of Zhejiang University-SCIENCE(A/B/C)are edited by the international board of distinguished Chinese and foreign scientists,and are aimed to present the latest developments and achievements in scientific research in China and overseas to the world’s scientific circles,especially to stimulate