基于移动用户上下文相似度的协同过滤推荐算法

该文面向移动通信网络领域的个性化服务推荐问题,通过将移动用户上下文信息引入协同过滤推荐过程,提出一种基于移动用户上下文相似度的改进协同过滤推荐算法。该算法首先计算基于移动用户的上下文相似度,以构造目标用户当前上下文的相似上下文集合,然后采用上下文预过滤推荐方法对移动用户-移动服务-上下文3维模型进行降维得到移动用户-移动服务2维模型,最后结合传统2维协同过滤算法进行偏好预测和推荐。仿真数据集和公开数据集实验表明,该算法能够用于移动网络服务环境下的用户偏好预测,并且与传统协同过滤相比具有更高的推荐精确度。     

基于上下文相似度和社会网络的移动服务推荐方法

针对传统的基于协同过滤的移动服务推荐方法存在的数据稀疏性和用户冷启动问题,提出一种基于上下文相似度和社会网络的移动服务推荐方法(Context-similarity and Social-network based Mobile Service Recommendation,CSMSR).该方法将基于用户的上下文相似度引入个性化服务推荐过程,并挖掘由移动用户虚拟交互构成的社会关系网络,按照信任度选取信任用户;然后结合基于用户评分相似度计算发现的近邻,分别从相似用户和信任用户中选择相应的邻居用户,对目标用户进行偏好预测和推荐.实验表明,与已有的服务推荐方法TNCF、SRMTC及CF-DNC相比,CSMSR方法有效地缓解数据稀疏性并提高推荐准确率,有利于发现用户感兴趣的服务,提升用户个性化服务体验.     

一种基于移动用户行为的回路融合社区发现算法

针对现有基于派系的重叠社区发现算法难以对移动社会化网络实施的问题,该文给出一种基于移动用户行为的回路融合社区发现算法。该算法首先通过分析移动用户行为构建移动社会化网络,利用k-EC(k-Elementary Circuit)简单回路发现算法寻找移动社会化网络的k阶回路作为社区核,并按照给定的规则对社区核进行融合,得到初步社区;然后通过计算移动用户行为的相关度将余下的离散节点加入到相应的初步社区,得到最终的社区;最后通过公开数据集和仿真数据集验证了该算法在移动社会化网络社区发现方面的可行性和有效性。     

基于云计算平台的图书馆混合推荐技术研究

研究基于云计算平台的图书馆混合推荐技术,向不同类型用户精准推荐图书。构建以并行计算框架为计算前提的图书馆混合推荐系统。采用Flume采集图书馆用户日志信息和图书馆图书数据,将采集到的数据信息传输到Kafka消息中间件后,向集群中传入集群订阅的数据信息,集群在用户粘稠度较低时采用聚类算法聚类图书馆数据信息,获取聚类中心,依照聚类中心用户读书偏好向目标用户推荐图书。在用户粘稠度较高时,采用基于协同过滤的混合推荐算法分析目标用户阅读偏好,计算目标用户偏好和用户群中用户偏好相似程度,将偏好相似程度作为权值,组合多个权值产生预测评分,通过预测评分推荐图书。经过实验分析发现,该方法推荐精准性最高为99.72%,推荐查准率高于95%,响应时间不超过0.2 s,说明该方法能高效快速地向目标用户推荐图书。     

移动网络服务中基于认知心理学的用户偏好提取方法

 迅速增长的移动网络服务给人们带来沉重的移动信息负担.移动用户偏好提取方法是缓解"移动信息过载"问题的有效手段.受加工水平模型和分布式认知理论的启发,提出一种基于认知心理学的移动用户偏好提取方法.在移动用户偏好信息结构建模的基础上,引入服务加工水平认知、有效上下文认知的概念,并计算其对用户偏好提取的影响,然后分别提取基于服务加工水平认知和基于有效上下文认知的用户偏好,最终提取综合的用户偏好.实验结果表明,该方法能有效提高移动用户偏好提取精确度,为用户提供满足个性化需求的移动网络服务.     

基于算力网络架构下的用户移动性分析

本文基于常用的用户移动性分析算法,在新一代算力网络架构下分析用户智能终端的位置数据得到用户移动偏好应用（移动热点、移动位置预测等）,充分利用算力网络,提高计算效率,平衡计算资源。同时,本文还分析了不同移动偏好的用户在用户移动偏好应用中的适配度。     

基于随机游走和多样性图排序的个性化服务推荐方法

针对传统服务推荐算法由于数据稀疏性而导致推荐准确性不高,以及推荐结果缺乏多样性等缺陷,提出基于随机游走和多样性图排序的个性化服务推荐方法（PRWDR）.在分析直接相似关系稀疏性的基础上提出带权重的随机游走模型,通过在用户网络上进行随机游走来挖掘更多的相似关系;基于所有相似用户预测服务的QoS值,并给出服务图模型构建方法,以过滤大量性能过低的候选服务;提出最优节点集合选取策略,利用贪婪算法得到兼具推荐准确性和功能多样性的服务推荐列表.在公开发布的数据集上进行实验,并与多个经典算法进行比较,验证了本算法的有效性.     

基于移动流量的用户偏好模型设计与实现

在智能手机市场快速发展的同时,也产生了大量的移动数据流量。这些流量反映了人们在手机上的浏览情况和个人喜好。文中使用DPI&DFI技术解析客户端使用流量情况,使用网络爬虫技术及分词技术解析网页访问信息,最后汇总整合解析出的流量数据信息。以数据信息为输入建立偏好模型,计算得到用户对每一类业务的喜爱程度分数。将分数汇总列为用户偏好清单,以用户手机号为标识,各个分类的得分为内容。将此结果用于对移动用户的流量经营,为用户提供符合其流量使用偏好的推荐内容,提升流量规模和收入。     

基于项目属性和BP神经网络的协同过滤推荐

针对协同过滤推荐中存在的数据稀疏性问题,文中提出了一种基于项目特征属性和BP神经网络相结合的协同过滤推荐算法,并通过Movielens数据集验证了该模型的有效性。此方法首先将用户评分数据映射为用户对项目特征属性的偏好,然后使用BP神经网络训练得到目标用户的特征属性偏好模型并对新项目的评分进行预测,从而降低用户项目评分矩阵的数据稀疏性,最后使用协同过滤推荐算法,形成最近邻并生成推荐建议。     

基于移动场景的复合推荐系统设计

本文将移动场景引入高校图书馆阅读推荐服务,在设计了适合移动场景阅读推荐的资源提供单元、阅读推荐单元、用户体验单元和推荐算法单元等四个系统单元的基础上,探讨了用户行为数据、用户场景数据和复合数据推荐的三个系统功能,最后,将移动场景的引入感知、社会网络关系、情感体验以及引入认知等四要素融入阅读推荐系统中并重新构建了阅读推荐...     

Cooperative caching game based on social trust for D2D communication networks

Content sharing via device‐to‐device (D2D) communications has become a promising method to increase system throughput and reduce traffic load. Due to the characteristic of spectrum sharing in D2D network, confidentiality is becoming a key issue in content transmission. Secure communication in D2D networks is generally guaranteed by a physical‐layer security mechanism. However, this method sacrifices the system transmission rate while ensuring security. Since mobile devices are carried by humans, we can leverage their trust relations to enhance the security of communications. As much, considering the psychology structure and social attributes of mobile users, we build a multidimensional trust evaluation mechanism to evaluate the trust relationship between users, and we pick out the trusted users based on the decision‐theoretic rough sets. By sharing content only between trust users, we can enhance the security of content transmissions without relying on physical‐layer security measures. Meanwhile, content caching is now widely used to improve accessing efficiency and reduce traffic load on cellular networks. However, caching content for other users incurs additional cost, which results in selfish and noncooperative behavior in users. Considering such selfishness, we introduce a cooperative caching game based on multidimensional trust relations to motivate users to cache contents for other devices. In this game, the trust relations and physical distance between two users are considered to formulate the cost function. Furthermore, we introduce an incentive caching algorithm based on social trust to minimize the total cost in the D2D network.     

基于在线拍卖的网络切片资源分配算法

为满足未来移动通信网络中多样化的业务需求,为用户提供定制化服务的同时提升网络经济效益,该文提出一种基于在线拍卖的网络切片资源分配算法。根据业务类型将用户的服务请求转化为相应投标信息,以最大化拍卖参与者的社会福利为目标,将切片资源分配问题建模为基于多业务的在线赢家确定问题。结合资源分配与价格更新策略,实现基于在线拍卖的资源优化配置。仿真结果表明,该算法能够在满足用户业务需求的同时,提升网络经济效益。     

A Semantics-based Approach to Large-Scale Mobile Social Networking

Mobile ad hoc social networks are self-configuring social networks that connect users using mobile devices, such as laptops, PDAs, and cellular phones. These social networks facilitate users to form virtual communities of similar interests or commonalities. This paper proposes semantics-based mobile social network (SMSN), a novel framework of a fully functional mobile ad hoc social network that incorporates semantics of users’ social data. SMSN provides effective and efficient solutions to social network construction, semantics-based user profile matching, multi-hop semantics-based routing, and privacy management. Moreover, SMSN is rigorously benchmarked using an elaborate simulation setup and released as a prototype system that can be run on cellular phones. Due to its generality, SMSN can be applied to a wide range of critical applications, such as disaster-recovery, homeland security, and personnel control.     

基于网络模体的移动社会网络信息可控传播方法

移动社会网络中的信息传播具有突发性、多元性、偏差性等特点,使得相关话题和事件能够在短时间内形成强大的网络和社会舆论场,这有可能被恶意用户利用来散布谣言,给网络环境带来了恶劣的影响。针对这一问题,该文提出一种基于网络模体的信息可控传播方法。首先,提出多实体的竞争性独立级联模型(MCIC),该模型在信息竞争扩散理论的基础上,首次结合社会网络层用户的社会属性,来感知恶意信息并控制信息传播。其次,该文定义了控制信息流模体(CIFM),并选择出具有可控传播功能的关键网络模体,设计其在通信层的高效可控传播算法。最后,通过理论推导证明了该文方法具有收敛性。仿真实验表明,与其他方法相比,所提方法不仅在信息传播中最大感染时间和平均感染时间上更有优势,而且在控制信息传播方面的效果也是最好的。     

Efficient Handover with Load Balancing: A Quality Perspective Approach

The heterogeneous wireless networking environment determined by the latest developments in wireless access technologies promises a high level of communication resources for mobile computational devices. Although the communication resources provided, especially referring to bandwidth, enable multimedia streaming to mobile users, maintaining a high user perceived quality is still a challenging task. The main factors which affect quality in multimedia streaming over wireless networks are mainly the error-prone nature of the wireless channels and the user mobility. These factors determine a high level of dynamics of wireless communication resources, namely variations in throughput and packet loss as well as network availability and delays in delivering the data packets. Under these conditions maintaining a high level of quality, as perceived by the user, requires a quality oriented mobility management scheme. Consequently a proposed smooth adaptive soft-handover algorithm, a novel quality oriented handover management scheme which unlike other similar solutions, smoothly transfer the data traffic from one network to another using multiple simultaneous connections.     

一种基于多跳D2D和社交感知的新颖中继选择算法

摘 要：将社交域引入蜂窝网络场景中的多跳设备到设备（device-to-device，D2D）通信中，并提出了一种用于蜂窝网络下多跳D2D通信的新颖中继选择算法。不同于以往的中继选择算法，所提出的算法以反向顺序选择每一跳的中继，减少了算法执行所产生的信令开销。在算法中引入了社交域信息，研究了社交域信息在多跳D2D通信中的作用。研究结果表明，终端用户之间的社交关系对算法性能具有不可忽略的影响，从而为实际系统的算法实现提供了一定的指导意义。另外，通过大量的蒙特卡洛仿真得到的结果表明，所提算法在不考虑社交关系信息时吞吐量和能量效率均优于对比算法，在考虑社交关系信息时，尽管其吞吐量会自然降低，但其能量效率远远优于对比算法。     

Intelligent Privacy Protection of End User in Long Distance Education

Long distance education is an important part during the COVID-19 age. An intelligent privacy protection with higher effect for the end users is an urgent problem in long distance education. In view of the risk of privacy disclosure of location, social network and trajectory of end users in the education system, this paper deletes the location information in the location set to protect the privacy of end user by providing the anonymous set to location. Firstly, this paper divides the privacy level of social networks by weighted sensitivity, and collects the anonymous set in social networks according to the level; Secondly, after the best anonymous set is generated by taking the data utility loss function as the standard, it was split to get an anonymous graph to hide the social network information; Finally, the trajectory anonymous set is constructed to hide the user trajectory with the l-difference privacy protection algorithm. Experiments show that the algorithm presented in this paper is superior to other algorithms no matter how many anonymous numbers there are, and the gap between relative anonymity levels is as large as 5.1 and 6.7. In addition, when the privacy protection intensity is 8, the trajectory loss rate presented in this paper tends to be stable, ranging from 0.005 to 0.007, all of which are less than 0.01. Meanwhile, its clustering effect is good. Therefore, the proportion of insecure anonymous sets in the algorithm in this paper is small, the trajectory privacy protection effect is good, and the location, social network and trajectory privacy of distance education end users are effectively protected.

     

The network paradigm of the 21st century and its key technologies

This article proposes a network paradigm called the single-server-view network as the basis for networks in the 21st century, when the value of a network to users will be based on the services provided rather than data communication capability. Based on our paradigm, we propose a double-plane network architecture, consisting of a simplified data forwarding plane and a service control plane, that performs all the complex processing tasks. The data forwarding plane uses an advanced photonic network as its basis. The service control plane consists of agent, service, and policy control layers with open interfaces between layers. Leading-edge information processing technologies, such as active node, agent, distributed processing, and policy-based management, are used in this plane. Since mobile communication is becoming a major access technology, an approach to integrating mobile and fixed networks into this framework is also proposed. The current status of key technologies, such as photonic networks, agent technology, and policy-based management, are reported.     

Maintaining weakly-connected dominating sets for clustering ad hoc networks

An ad hoc network is a multihop wireless communication network supporting mobile users. Network performance degradation is a major problem as the network becomes larger. Clustering is an approach to simplify the network structure and thus alleviate the scalability problem. One method that has been proposed to form clusters is to use weakly-connected dominating sets [Y.P. Chen, A.L. Liestman, Approximating minimum size weakly-connected dominating sets for clustering mobile ad hoc networks, in: The Third ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc’02), 2002, pp. 165–172; Y.P. Chen, A.L. Liestman, A zonal algorithm for clustering ad hoc networks, International Journal of Foundations of Computer Science 14(2) (2003) 305–322]. Here, we present a zonal distributed algorithm to maintain weakly-connected dominating sets as the network structure changes. When the zones are small, the algorithm is essentially localized; when the zones are large, it behaves more globally. The size of the weakly-connected dominating set obtained also varies depending on the choice of zone size, with larger zones generally resulting in smaller weakly-connected dominating sets. Experiments provide evidence that this maintenance algorithm keeps the size of the weakly-connected dominating set approximately the same as its initial size and does not compromise the network connectivity.