基于朋友关系变迁演化的社区划分算法

机会网络中的节点大多是由人携带的具有短距离无线通信能力的设备,因此节点具有人的社会属性,机会网络也具有社区特性。而现有的社区划分算法多数来源于社会网络,不能直接用于节点稀疏、网络拓补结构不断不化、节点的计算和存储资源有限的机会网络中。本文通过提出节点的朋友关系,利用节点自身的相遇历史信息,将网络划分为不同的朋友社区。在两种不同数据集下的实验结果表明朋友社区的划分可有效减低路由开销,同时保持较高的传输成功率。     

Finding Diachronic Like‐Minded Users

User communities in social networks are usually identified by considering explicit structural social connections between users. While such communities can reveal important information about their members such as family or friendship ties and geographical proximity, just to name a few, they do not necessarily succeed at pulling like‐minded users that share the same interests together. Therefore, researchers have explored the topical similarity of social content to build like‐minded communities of users. In this article, following the topic‐based approaches, we are interested in identifying communities of users that share similar topical interests with similar temporal behavior. More specifically, we tackle the problem of identifying temporal (diachronic) topic‐based communities, i.e., communities of users who have a similar temporal inclination toward emerging topics. To do so, we utilize multivariate time series analysis to model the contributions of each user toward emerging topics. Further, our modeling is completely agnostic to the underlying topic detection method. We extract topics of interest by employing seminal topic detection methods; one graph‐based and two latent Dirichlet allocation‐based methods. Through our experiments on Twitter data, we demonstrate the effectiveness of our proposed temporal topic‐based community detection method in the context of news recommendation, user prediction, and document timestamp prediction applications, compared with the nontemporal as well as the state‐of‐the‐art temporal approaches.     

A Calculus of Virtual Community Knowledge Intentions: Anonymity and Perceived Network-Structure

This study investigates the underlying motivational factors of knowledge exchange intentions (intention to obtain and to provide knowledge) within virtual community contexts. Perceived virtual network structures, namely virtual network connectivity (CN) and virtual network closeness (CL), are suggested as the important antecedents of knowledge sharing intentions in the context of virtual knowledge exchange communities. Anonymity (AN), one of the unique characteristics of virtual communities, but controversial due to its multi-faceted effects, is considered in a structural model as a factor having an impact on a virtual network structure. Data collected from participants of virtual communities through online surveys are analyzed using Partial Least Squares (PLS) structural equation modeling (SEM) to empirically test the proposed hypotheses. The results reveal that both CN and CL have a significant impact on both of the knowledge exchange intentions although CL shows an opposite direction of the impact. The results also show that AN has a significant impact on CL as expected but not on CN. Implications of this study may shed some light on better understanding community participants’ intentions to obtain and provide knowledge, along with the impact of anonymity on the perceived network structure.     

Wired mobile phones: the case of community technology centers in favelas of Brazil*

ABSTRACT

The growing spread of mobile phones and internet has some practitioners and scholars arguing about the possible irrelevance of community technology centers (CTCs) serving low-income communities. However, although mobile internet is making great strides, it does not yet substitute for public access; in actuality, mobile phones and computers at CTCs complement each other in providing those who face digital inequalities with a broader sociotechnical experience. In order to explore this problem, this paper explores this experience by investigating how favela residents appropriate mobile phones, posing the question, “how do marginalized populations perceive CTCs in the mobile internet era?” To address this question, I draw on a 10-month ethnography in the favelas of Vitória, Brazil which examines slum residents’ uses of information and communication technologies (ICTs) such as computers and smartphones. Through this research, I demonstrate how marginalized people take advantage of smartphones and computers in a complementary way, using these ICTs to best meet their needs as they experience daily life in a relatively severe environment.     

A mobile edge computing-based applications execution framework for Internet of Vehicles

Mobile edge computing (MEC) is a promising technology for the Internet of Vehicles, especially in terms of application offloading and resource allocation. Most existing offloading schemes are sub-optimal, since these offloading strategies consider an application as a whole. In comparison, in this paper we propose an application-centric framework and build a finer-grained offloading scheme based on application partitioning. In our framework, each application is modelled as a directed acyclic graph, where each node represents a subtask and each edge represents the data flow dependency between a pair of subtasks. Both vehicles and MEC server within the communication range can be used as candidate offloading nodes. Then, the offloading involves assigning these computing nodes to subtasks. In addition, the proposed offloading scheme deal with the delay constraint of each subtask. The experimental evaluation show that, compared to existing non-partitioning offloading schemes, this proposed one effectively improves the performance of the application in terms of execution time and throughput.     

融合K-shell和标签熵的重叠社区发现算法

针对标签传播算法稳定性不足、准确性较差的问题,提出了融合K-shell和标签熵的标签传播重叠社区发现算法OCKELP。首先,采用K-shell算法减少了标签初始化时间,并利用标签熵的更新序列提高了算法的稳定性;其次,引入综合影响力进行标签选择,并将社区层次信息和节点局部信息融合提高了算法的准确性。在真实网络数据集上,OCKELP相较于重叠社区发现算法（COPRA）、基于多核心标签传播的重叠社区识别方法（OMKLP）、SLPA的模块度最大提升分别约68.64%、53.99%、42.29%,在人工网络数据集的归一化互信息（NMI）值上,OCKELP相较于其他三种算法也有着明显优势,且随着重叠节点隶属社区数量的增加可以挖掘出社区的真实结构。     

基于改进DBSCAN算法的汽车行驶热区提取方法

随着我国汽车工业的飞速发展,汽车消费迅速膨胀,汽车市场竞争日益加剧.合理选择汽车销售及售后区域对汽车厂家有着十分重要的影响,对重卡车辆生产厂家的影响更加明显.采用车载GPS技术和改进的DBSCAN算法将陕重汽的不同类型车辆的行驶GPS数据进行空间聚类分析,最终得到不同车辆的活动热点地区分布数据;分析得到的数据对今后车辆的设计、销售及售后的相关决策问题有着重要的参考价值.     

三峡库区城镇移民小区综合帮扶绩效评价研究

为衡量三峡库区城镇移民小区综合帮扶过程的效率及其成果的有效性,通过辨析综合帮扶绩效评价内涵,对其绩效评价层级和维度进行了划分,并从管理、产出和效益3个维度构建了绩效评价指标体系,明确了指标权重系数的确定方法及其计算方法。通过绩效评价指标体系的构建以及评价方法的确定,为小区综合帮扶管理部门提供了开展帮扶绩效评价的途径和依据。研究结果表明,城镇移民小区综合帮扶绩效评价具有财政性、项目性、区域性和管理性特点,可为三峡库区后续工作其他项目实施绩效评价提供借鉴和参考。     

渭河流域水生态系统群落结构特征及其健康评价

以渭河流域为对象,基于77个点位的水生态采样和调查结果,分析了该流域干支流着生藻类、大型底栖动物和鱼类3种生物类群群落结构特征,采用生物完整性指数评价了渭河流域鱼类、大型底栖动物和着生藻类的完整性,并对3种生物类群进行评价分析与比较。结果表明:基于3种生物类群的水生态系统健康评价结果存在一定差异,主要是由于3种生物类群对环境变化的响应各有不同,其中大型底栖动物的评价结果最好,其次为着生藻类,鱼类健康评价结果最差。综合来看,渭河流域水生态系统健康状况较差,受人类活动影响明显,大体表现为从上游到下游健康状况越来越差的趋势。对于渭河流域,影响鱼类、大型底栖动物和着生藻类的环境因子各有不同。通过系统全面地调查分析渭河流域不同生物类群的群落结构,可为流域水生态系统恢复提供科学依据。