Defending recommender systems by influence analysis

Collaborative filtering (CF) is a popular method for personalizing product recommendations for e-commerce applications. In order to recommend a product to a user and predict that user’s preference, CF utilizes product evaluation ratings of like-minded users. The process of finding like-minded users forms a social network among all users and each link between two users represents an implicit connection between them. Users having more connections with others are the most influential users. Attacking recommender systems is a new issue for these systems. Here, an attacker tries to manipulate a recommender system in order to change the recommendation output according to her wish. If an attacker succeeds, her profile is used over and over again by the recommender system, making her an influential user. In this study, we applied the established attack detection methods to the influential users, instead of the whole user set, to improve their attack detection performance. Experiments were conducted using the same settings previously used to test the established methods. The results showed that the proposed influence-based method had better detection performance and improved the stability of a recommender system for most attack scenarios. It performed considerably better than established detection methods for attacks that inserted low numbers of attack profiles (20–25 %).     

Detecting shilling attacks in private environments

Privacy-preserving collaborative filtering algorithms are successful approaches. However, they are susceptible to shilling attacks. Recent research has increasingly focused on collaborative filtering to protect against both privacy and shilling attacks. Malicious users may add fake profiles to manipulate the output of privacy-preserving collaborative filtering systems, which reduces the accuracy of these systems. Thus, it is imperative to detect fake profiles for overall success. Many methods have been developed for detecting attack profiles to keep them outside of the system. However, these techniques have all been established for non-private collaborative filtering schemes. The detection of shilling attacks in privacy-preserving recommendation systems has not been deeply examined. In this study, we examine the detection of shilling attacks in privacy-preserving collaborative filtering systems. We utilize four attack-detection methods to filter out fake profiles produced by six well-known shilling attacks on perturbed data. We evaluate these detection methods with respect to their ability to identify bogus profiles. Real data-based experiments are performed. Empirical outcomes demonstrate that some of the detection methods are very successful at filtering out fake profiles in privacy-preserving collaborating filtering schemes.     

电子阅览室维护经验

介绍了电子阅览室计算机系统维护的三种方法。这几种维护方法 ,既有单机系统维护 ,又有网络维护 ,对系统维护人员具有极高的参考价值。本文不仅讨论系统维护理论 ,还就维护方法列出了详细操作步骤。     

关于文献分类学研究对象问题的思考

文献分类学是研究图书馆文献分类的原理、方法、规律和应用等问题,以方便人们按学科知识系统管理和利用文献的一门学科。文献分类学的研究对象主要是文献分类法或是网络信息分类法,这两种观点值得商榷。     

科技信息中关系数据的可视化研究

在不同领域,随着数据规模的日益扩大,对于数据的自动分析技术已变得不可或缺。人们通过数据挖掘技术可以更高效地得到大规模数据的各种特征。在知识发现的过程中,无论对于数据分析还是数据挖掘,可视化都是将数据中的特征转换为知识的关键步骤。文章将从可视化分析与信息可视化的角度概述在科技信息领域中关系数据的可视化分析方法及其应用。首先,文章介绍在科技信息领域可视化的相关方法,以及信息可视化的特点与局限;接着介绍可视化分析在科技信息领域的相关工具与系统;最后给出一个对我国生命科学领域论文同被引网络的可视化分析实例。通过对该同被引网络的可视化分析,可以很直观地发现在该研究领域的不同研究方向以及引领这些研究方向的主要论文及其关系。     

网络信息的入侵检测技术与方法研究

随着计算机网络的广泛应用，非法的入侵与攻击行为不断发生，严重威胁着网络信息的安全，对入侵和攻击进行检测与防范，保障计算机系统、网络系统及整个信息基础设施的安全已经成为刻不容缓的重要课题。本文针对网络信息的入侵检测技术与方法进行讨论和研究，并对入侵与入侵检测的技术趋势进行探讨。     

Network technologies for information warfare and manipulation of public opinion

This paper explores the impact of new information technologies on the development of social communication and social systems. The properties and features of the modern information environment are analyzed. The factors and technologies of information warfare and confrontation are investigated. The role of information communication technologies in the operation of social-network movements is demonstrated. The means and methods of the mass media, social networks, and destructive network technologies that are applied to manipulate group behavior and to transform public opinion are exposed. The potential of sociodynamics as a new instrument of targeted impact on social systems is explored. Possible risks and threats that face the development of telecommunication systems and networks are assessed. Conclusions and relevant activities are formulated to prevent the rise of information confrontations and to mitigate hidden impacts and threats to the country’s social-economic, scientific, and technological development.     

基于属性论的馆藏文献自助借还管理系统

论述计算机及辅助管理系统在当前的文献开架管理工作中存在的技术问题,阐述属性论关于事物特征获取的过程, 提出选取相应的条形码、重量、指纹、视图等数字化属性检测技术,建立以计算机网络为核心的馆藏文献自助借还集成管理系统－Self-ABRS,并简要介绍其功能、流程及工作原理。     

对维护网络安全运用入侵检测技术的研究

介绍入侵检测的方法,分析入侵检测系统的功能,列举现有入侵检测系统的主要类型,阐述入侵检测技术的发展状况。     

Detecting and assessing statistical interactions with multiple regression

This paper focuses on the treatment of statistical interactions (i.e., non‐additivity) within the framework of multiple regression. The nature of statistical interactions in relation to other types of effects and the implications of interactions for analysis and interpretation are discussed. We argue that researchers using regression analyses (1) often either fail to test for interactions (2) or use inadequate methods for testing for interactions (3) and, consequently may make faulty conclusions about their data. We outline several methods of dealing with interactions with regression and discuss the strengths and weaknesses of each. Recommendations are made for the detection and treatment of interactions within regression.     

医学研究生文献检索课教学改革初探

从教学内容、教学方法以及考核方式三个方面对网络环境下的医学研究生文献检索课教学改革进行了探讨。参考文献7。     

Assessing Deception Detection Accuracy with Dichotomous Truth–Lie Judgments and Continuous Scaling: Are People Really More Accurate When Honesty Is Scaled?

Deception detection experiments consistently find that people are only slightly better than chance at distinguishing truths from lies. Interpersonal deception theory research, however, claims that people can accurately detect deception when honesty is assessed with continuous scaling. This article reports an experiment (N = 140) directly testing if the type of measurement meaningfully impacts accuracy results and conclusions. The findings suggest that the difference is largely illusory, and that the differences that are observed are attributable to differential variances in the measures. Substantively, both methods yield similar conclusions including slightly better-than-chance accuracy, persistent truth bias, and a robust veracity effect.     

基于层次任务分析的社交网站信息构建评估 ——以花瓣网为例

在综合比较三种网站信息构建评估方法的基础上,采用层次任务分析与用户测试相结合的方法对社交网站的信息构建进行系统分析与评估,以社交分享类网站——花瓣网为例:首先构建花瓣网层次任务图与行动计划,然后进行用户任务测试,使用4种度量指标对测试数据进行标准化处理,最后得出网站信息构建评估分数,发现该网站信息构建中存在的问题。     

基于中心第三层交换VLAN的图书馆Intranet体系

详细阐述VLAN的应用优势及划分策略,对VLAN间的通讯和中心第三层交换机的原理及应用优势进行科学分析,进而提出基于中心第三层交换VLAN是图书馆大型网络体系的一个最佳选择;着重从多层交换网络体系的构建、VLAN的合理规划、采用安全有效管理策略三个方面,对图书馆Intranet体系的构建进行探讨。     

移动图书馆用户采纳行为的整合模型实证研究

基于传统信息系统采纳模型,结合心理学和行为科学相关理论,从一般技术因素、特定技术因素、用户心理因素和社会影响因素四个方面构建了一个整合的移动图书馆用户采纳行为的结构方程模型,并且采用SPSS 17．0和PLS结构方程软件对模型和假设进行检验。实证结果表明：感知易用性、感知移动性、用户创新性、感知信任和网络外部性是影响用户采纳移动图书馆的主要因素,而感知有用性、感知货币价值和社会规范对用户采纳移动图书馆的影响不显著。     

IAIMS at Columbia-Presbyterian Medical Center: accomplishments and challenges.

The concept of "one-stop information shopping" is becoming a reality at Columbia-Presbyterian Medical Center. Our goal is to provide access from a single workstation to clinical, research, and library resources; university and hospital administrative systems; and utility functions such as word processing and mail. We have created new organizational units and installed a network of workstations that can access a variety of resources and systems on any of seventy-two different host computers/servers. In November 1991, 2,600 different individuals used the clinical information system, 700 different individuals used the library resources, and 900 different individuals used hospital administrative systems via the network. Over the past four years, our efforts have cost the equivalent of $23 million or approximately 0.5% of the total medical center budget. Even small improvements in productivity and in the quality of work of individuals who use the system could justify these expenditures. The challenges we still face include the provision of additional easy-to-use applications and development of equitable methods for financial support.     

基于图挖掘的文本主题识别方法研究综述

本文通过文献调研分析,将基于图挖掘的文本主题识别方法总结为中心度方法、紧密关联子图查找和图聚类三种,后两者又细分为基于clique子团或类clique子团、基于图拓扑结构或结点属性聚类的方法。中心度方法通过对比文本网络中术语结点的重要度来实现文本主题的识别,紧密关联子图查找和图聚类方法则是根据文本图中术语结点和边的属性相似度来识别文本核心主题。基于语言文本网络自身特性,如何构建复杂文本关系图来同时揭示术语间的句法、共现和语义关系,如何基于术语关联和图拓扑结构识别其中的紧密关联子团,基于何种标准将紧密关联子团聚类以揭示文本核心主题,都是未来需要进一步深入研究的问题。表1。     

谈构建馆藏文献保护的技术防线

文献检测系统是防止馆藏人为侵害的应用管理系统,是文献安全管理系统的组成部 分。文献检测系统分为属性检测、非属性检测两大类。馆藏文献人为侵害防止,应以人防为主, 技术防范为辅。参考文献6。     

Optimizing SCImago Journal & Country Rank classification by community detection

Subject classification arises as an important topic for bibliometrics and scientometrics, searching to develop reliable and consistent tools and outputs. Such objectives also call for a well delimited underlying subject classification scheme that adequately reflects scientific fields. Within the broad ensemble of classification techniques, clustering analysis is one of the most successful.Two clustering algorithms based on modularity – the VOS and Louvain methods – are presented here for the purpose of updating and optimizing the journal classification of the SCImago Journal & Country Rank (SJR) platform. We used network analysis and Pajek visualization software to run both algorithms on a network of more than 18,000 SJR journals combining three citation-based measures of direct citation, co-citation and bibliographic coupling. The set of clusters obtained was termed through category labels assigned to SJR journals and significant words from journal titles.Despite the fact that both algorithms exhibited slight differences in performance, the results show a similar behaviour in grouping journals. Consequently, they are deemed to be appropriate solutions for classification purposes. The two newly generated algorithm-based classifications were compared to other bibliometric classification systems, including the original SJR and WoS Subject Categories, in order to validate their consistency, adequacy and accuracy. In addition to some noteworthy differences, we found a certain coherence and homogeneity among the four classification systems analysed.     

Scheduling cooperative transactions in distributed database systems

Scheduling transactions in advanced applications of distributed database systems, such as real-time distributed groupware systems and network management systems, are different from that in traditional database systems. In this paper, we propose new scheduling models, LWL for coordinating cooperative activities in real-time distributed groupware systems, and GTM for providing interoperability to network management systems, respectively.