CSDN——三年铸成的平台

《程序员》的东家——www.csdn.net,在本月就三周岁了。是谁开辟了中国最大的开发者网络？面对网站寒冬,CSDN将如何发展？你可以在《CSDN——三年铸成的平台》中找到答案。     

言论

声音●我们非常抱歉发生的部分用户信息泄露事件,为了加强用户信息安全,我们将对用户信息中存在安全隐患(包括:密码过于简单等情况)的CSDN帐号,进行临时锁定。——中国开发者技术在线社区CSDN发表声明,     

基于知识图谱和重启随机游走的跨平台用户推荐方法

针对单一社交网络平台中推荐相似用户结果单一,对用户兴趣和行为信息了解不够全面的问题,提出了基于知识图谱和重启随机游走的跨平台用户推荐方法（URCP-KR）。首先,在分割、匹配出的目标平台图谱和辅助平台图谱的相似子图中,利用改进的多层循环神经网络（RNN）预测出候选用户实体,再综合利用拓扑结构特征相似度和用户画像相似度筛选出相似用户;然后,将辅助平台图谱中的相似用户的关系信息补全到目标平台图谱;最后,计算目标平台图谱中的用户游走到社区内每个用户的概率,从而得到用户之间的兴趣相似度来实现用户推荐。实验结果表明,与协同过滤（CF）算法、基于跨平台的在线社交网络用户推荐算法（URCP）和基于多开发者社区的用户推荐算法（UR-MC）相比,URCP-KP在推荐精确率及推荐多样性等方面均有所提高,推荐精确率最高可达95.31%,推荐覆盖率最高可达88.42%。     

新书上架

5月17日,本刊编辑部＆CSDN 网站在北京工业大学举行了今年第一次大规模的读者见面会。《程序员》和 CSDN 网站的主要负责人及版块编辑,在细雨纷飞中来到清新的北工大,与来自北京十多所高校的学生进行零距离交流。整个见面会在一种轻松的气氛中进行,提问、互动、发奖、自由交流,摄影,气氛相当热烈。会议期间,杂志社社长蒋涛在介绍杂志和网站历史、定位及目前     

大学生中的CSDN专家——记廊坊师范学院信息技术提高班中的大学生

<正>CSDN与CSDN专家CSDN是中国最大的开发者技术社区。它是集新闻、论坛、群组、Blog、文档、下载、读书、Tag、网摘、搜索、.NET、Java、游戏、视频、人才、外包、第二书店等多种项目于一体的大型综合性IT门户网站,有很强的专业性,其会员囊括了中国地区百分之九十以上的优秀程序员,在IT技术交流及其周边国内中是第一位的网站。CSDN在全球范围内注册用户超过1 800     

针对复杂用户评论的代码质量属性判断

随着开发者社区和代码托管平台成为程序员获取代码的主要途径,针对代码的用户评论数量急剧增加.用户在使用代码后给出的评论中包含多种静态和动态的代码质量属性信息,但是由于用户评论多为复杂句,使得评论中包含的代码质量属性难以判断.针对复杂用户评论的代码质量属性判断将有助于分析用户评论中的代码质量信息,有助于开发者在了解用户的代...     

CSDN带高校生走进企业实践——CSDN创始人和董事长蒋涛先生专访

互联网技术的迅猛发展,带来了市场对科技人才需求的不断变化。高校如何顺应市场变化需求,建立有效的人才培养机制?校企合作、产教结合,应该是很多高校普遍采用的策略。早在互联网发展方兴未艾之时,CSDN就开始致力于为开发者提供学习交流平台,见证了一波又一波的技术浪潮,对技术发展趋势有着敏锐的洞察力。如今,CSDN已由技术社区发展成开发者服务平台,为中国的软件开发者和IT从业者提供知识传播、职业发展、软件开发等全生命周期服务。一直以来,CSDN与高校有着紧密的联系与合作。CSDN专门成立了高校俱乐部,面向高校的计算机院系师生,并联合企业绘制市场紧缺技术人才的成长路径、技能图谱,吸纳CSDN旗下大量优质资源,如企业实战培训课程、代码托管服务、开源项目、定制化知识服务,通过更有趣的"学习+社交"学习形式,让在校大学生"有的学"且"有计划高效的学"。同时,高校俱乐部还联合行业伙伴,开展有关教育的行业会议,增强教师与行业的交流。近期,围绕校企合作模式、人才培养、市场需求动向、大学生创业等方向,《计算机教育》杂志奚春雁主编(以下简称奚)专访了CSDN创始人蒋涛董事长(以下简称蒋)。     

云服务传递网络研究进展

云服务传递网络(Cloud Services Delivery Networks,CSDN)在Internet之上构建了一层分布式服务器网络,以就近和按需的方式向用户提供云传递服务。互联网流量的非线性快速增长及其表现出的视频化、移动化和交互化等特点,使得以提供高效、可信云传递服务为目标的CSDN面临诸多新挑战。首先在介绍和分析CSDN背景与新挑战的基础上,从基础设施层、平台层和服务层等3个维度提出了一个现有相关技术的分类模型。然后全面综述了CS-DN相关技术的最新研究现状,包括节点内组网、服务器部署、内容命名、内容管理、请求解析和系统管理等。最后指出了CSDN的未来研究趋势,即CSDN亟需突破的新技术问题,包括协同、移动管理和交互支持等。     

基于iOS平台的自定义手势识别研究

基于iOS应用开发过程中经常需要用到用户自定义手势识别功能．但是iOSAPI仅仅提供了简单的手势功能,不能满足开发者要求。基于向量统计和正则表达式的自定义手势识别算法实现了复杂的用户自定义手势识别功能,并在iOS平台实现了该算法。     

概率图模型在社交网络用户相似性发现中的应用

社交网络中的用户相似性发现作为社交媒体数据分析中的基础研究,可以应用于基于用户的商品推荐以及社交网络中推导用户关系演化过程等。为了有效地描述社交网络用户间复杂的相关性及不确定性,并从理论上提高海量社交网络用户相似性发现的准确度,研究了基于贝叶斯网这一重要的概率图模型,结合网络拓扑结构和用户之间的依赖程度,发现社交网络用户相似性的方法。为了提高算法的可扩展性,解决海量数据带来的存储和计算问题,提出了基于Hadoop平台的贝叶斯网分布式存储以及并行推理方法。最后通过实验结果验证了算法的高效性和正确性。     

Better the devil you know: Inter-organizational information technology and network social capital in coopetition networks

By enabling more efficient information and knowledge sharing and reinforcing the shared goals for participating members, inter-organizational information technology (IT) becomes instrumental to both accomplishing coopetitive outcomes and avoiding the pitfalls of partner opportunism. We posit that as network social capital is accumulated in technology-enabled coopetition networks, collaboration will enhance the strategic value of outcomes and positively affect goal convergence among network users. Our findings illustrate that the role of technology in coopetition extends beyond facilitating knowledge exchange and may play a vital role in the strategic development of firms pursuing coopetitive options.     

基于桥梁用户的多社交网络影响最大化

单社交网络影响最大化问题已经得到了学术界的广泛关注与研究,然而如今多社交网络之间呈现信息互通的趋势.多社交网络中存在的桥梁用户（Bridge User,BU）（即同时拥有多个社交网络账户的用户）,可将信息从一个社交网络分享至另外一个社交网络,信息传播不再局限于单个网络.本文针对多社交网络信息影响最大化进行了相关研究,分析了桥梁用户在多社交网络信息传播中的作用,提出了基于桥梁用户的多社交网络聚合算法,并在得到的聚合图上对多社交网络影响最大化问题进行求解.仿真实验对多社交网络影响最大化问题进行了求解,并证实了桥梁用户在多社交网络信息传播时的作用.     

Multi-relational reinforcement for computing credibility of nodes

Nowadays, growing number of social networks are available on the internet, with which users can conveniently make friends, share information, and exchange ideas with each other. As the result, large amount of data are generated from activities of those users. Such data are regarded as valuable resources to support different mining tasks, such as predicting friends for a user, ranking users in terms of their influence on the social network, or identifying communities with common interests. Traditional algorithms for those tasks are often designed under the assumption that a user selects another user as his friend based on their common interests. As a matter of fact, users on a social network may not always develop their friends with common interest. For example, a user may randomly select other users as his friends just in order to attract more links reversely from them. Therefore, such links may not indicate his influence. In this paper, we study the user rank problem in terms of their ‘real’ influences. For this sake, common interest relationships among users are established besides their friend relationships. Then, the credible trust link from one node to another is on account of their similarities, which means the more similar the two users, the more credible their trust relation. So the credibility of a node is high if its trust inlinks are credible enough. In this work, we propose a framework that computes the credibility of nodes on a multi-relational network using reinforcement techniques. To the best of our knowledge, this is the first work to assess credibility exploited knowledge on multi-relational social networks. The experimental results on real data sets show that our framework is effective.     

Joint user knowledge and matrix factorization for recommender systems

Currently, most of the existing recommendation methods treat social network users equally, which assume that the effect of recommendation on a user is decided by the user’s own preferences and social influence. However, a user’s own knowledge in a field has not been considered. In other words, to what extent does a user accept recommendations in social networks need to consider the user’s own knowledge or expertise in the field. In this paper, we propose a novel matrix factorization recommendation algorithm based on integrating social network information such as trust relationships, rating information of users and users’ own knowledge. Specifically, since we cannot directly measure a user’s knowledge in the field, we first use a user’s status in a social network to indicate a user’s knowledge in a field, and users’ status is inferred from the distributions of users’ ratings and followers across fields or the structure of domain-specific social network. Then, we model the final rating of decision-making as a linear combination of the user’s own preferences, social influence and user’s own knowledge. Experimental results on real world data sets show that our proposed approach generally outperforms the state-of-the-art recommendation algorithms that do not consider the knowledge level difference between the users.     

Resource-aware protocols for authenticated group key exchange in integrated wired and wireless networks

Protocols for group key exchange are cryptographic algorithms that describe how a group of parties communicating over a public network can come up with a common secret key. Due to their critical role in building secure multicast channels, a number of group key exchange protocols have been proposed over the years in a variety of settings. However despite many impressive achievements, there seems to have been no previous systematic look at the growing problem of key exchange over integrated wired and wireless (IWW) networks which consist of two distinct types of users: users having low-performance mobile devices with some form of battery power and users having high-performance stationary computers with no power constraint. The contribution of the present work is to fill this deficiency by providing a secure and efficient protocol for resource-aware group key exchange over the rapidly expanding IWW networks. By evenly spreading much of the total amount of computation across high power users, our protocol avoids any potential performance bottleneck of the system while keeping the burden on low power users at minimal. Our protocol also achieves provable security against powerful active adversaries under the decisional Diffie-Hellman assumption. We provide a rigorous proof of security for the protocol in a well-defined formal model of communication and adversarial capabilities.     

An efficient model for dimensioning an ATA-based virtual storage system

Internet Advanced Technology Attachment (iATA) is a block-level storage network protocol used by iATA servers to offer a storage solution for clients. With iATA, mobile users can access their valuable data through the network from anywhere and at anytime as if the storage device is attached locally. In the iATA architecture, iATA servers and iATA clients exchange necessary protocol messages over IP networks.     

基于图注意力网络表示学习的协同过滤推荐算法

针对传统的基于模型的协同过滤推荐算法未能有效利用用户与项目的属性信息以及用户之间与项目之间的关系结构信息, 本文提出一种基于图注意力网络表示学习的协同过滤推荐算法. 该算法使用知识图谱表示节点的属性特征信息和节点间的关系结构信息, 并在用户和项目的同质网络上进行节点的图注意力网络表示学习, 得到用户和项目的网络嵌入特征表示, 最后构建融合网络嵌入信息的神经矩阵分解模型获得推荐结果. 本文在Movielens数据集上与相关算法进行对比实验, 实验证明该算法能优化模型的推荐性能, 提高推荐的召回率HR@K和归一化折损累计增益NDCG@K.     

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。     

Simple password-based three-party authenticated key exchange without server public keys

Password-based three-party authenticated key exchange protocols are extremely important to secure communications and are now extensively adopted in network communications. These protocols allow users to communicate securely over public networks simply by using easy-to-remember passwords. In considering authentication between a server and user, this study categorizes password-based three-party authenticated key exchange protocols into explicit server authentication and implicit server authentication. The former must achieve mutual authentication between a server and users while executing the protocol, while the latter only achieves authentication among users. This study presents two novel, simple and efficient three-party authenticated key exchange protocols. One protocol provides explicit server authentication, and the other provides implicit server authentication. The proposed protocols do not require server public keys. Additionally, both protocols have proven secure in the random oracle model. Compared with existing protocols, the proposed protocols are more efficient and provide greater security.     

Multiagent-based knowledge networks

In this article, we present an approach for the design and development of knowledge networks and corporate memories based on Multi-Agent Systems (MAS) technology. A corporate memory is conceptualized as a network of agents that collaborate to provide the users with knowledge services for both intranets and the Internet. Lessons learned from the introduction of knowledge management practices into organizations are presented. These lessons have influenced and driven the MAS approach to knowledge networks and corporate memories described in this paper. An implementation of the RICA system (Knowledge and Information Networks with Agents), which incorporates these ideas, is presented.