小众社交 直面目标用户简

小众社交不比拥有海量用户的Twitter、微博,它们凭借自己独特的魅力吸引用户并维持着独特的关系。     

大数据让数据仓库更具价值简

Hadoop和MapReduce等这些新兴技术并不能解决数据相关的所有问题,作为一种传统技术,数据仓库在大数据时代依然焕发自己的活力。     

影讯简

杰瑞·尤斯曼与玛姬·泰勒夫妇的作品里,任何一个单位元素,云朵、湖水、树木、蜜蜂、斑马……都是我们再熟悉不过的,这些都是构成真实世界的真实元素。但是两位摄影师打乱了物体原本的规律,在视觉上运用真实的元素把我们带入了另外一个内心的“真实”世界。     

Ambient awareness: From random noise to digital closeness in online social networks

Ambient awareness refers to the awareness social media users develop of their online network in result of being constantly exposed to social information, such as microblogging updates. Although each individual bit of information can seem like random noise, their incessant reception can amass to a coherent representation of social others. Despite its growing popularity and important implications for social media research, ambient awareness on public social media has not been studied empirically. We provide evidence for the occurrence of ambient awareness and examine key questions related to its content and functions. A diverse sample of participants reported experiencing awareness, both as a general feeling towards their network as a whole, and as knowledge of individual members of the network, whom they had not met in real life. Our results indicate that ambient awareness can develop peripherally, from fragmented information and in the relative absence of extensive one-to-one communication. We report the effects of demographics, media use, and network variables and discuss the implications of ambient awareness for relational and informational processes online.     

ORDBMS中继承层次查询的设计与实现

文章针对新型工程数据库系统－对象－关系数据库的面向对象的特点,研究了复杂对象的继承机制,设计了对继承层次查询的方法,并在工程数据库ANGEL－Ⅱ中实现了该设计。     

基于引用机制的ORDBMS复杂对象查询

针对对象-关系数据库的特点,研究了复杂对象的引用机制,设计了处理包含引用表的复杂对象查询的方法,并在工程数据库ANOEL,Ⅱ中成功地实现了该设计。     

在VB6.0中用DATAGRID控件实现数据库查询

本文详细介绍了利用ＤａｔａＧｒｉｄ 控件和 ＣｏｍｂｏＢｏｘ控件联合起来实现数据库查询的一种方法。     

Exploring and mitigating social loafing in online communities

The motivation to share members’ knowledge is critical to an online community’s survival and success. Previous research has established that knowledge sharing intentions are based on group cohesion. Several studies also suggested that social loafing behavior will seriously corrode group cohesion. Therefore, social loafing is a key obstacle to fostering online community development. Although substantial studies have been performed on the critical factors that affect social loafing in the learning group, those on online communities are still lacking. By integrating two perspectives, social capital and perceived risk, a richer understanding of social loafing behavior can be gained. In the research model, social ties and perceived risk have been driven by anonymity, offline activities, knowledge quality, and media richness. Social ties and perceived risk are hypothesized to affect social loafing in the online community, which, in turn, is hypothesized as negatively affecting group cohesion. Data collected from 323 online users in online communities provide support for the proposed model. The study shows that social loafing is a significant negative predictor of the users’ group cohesion. The study also shows that social ties and perceived risk are important components of social loafing. Anonymity, offline activities, knowledge quality, and media richness all have strong effects on social ties and perceived risk in the online community. Implications for theory and practice and suggestions for future research are discussed.     

Finding email correspondents in online social networks

Email correspondents play an important role in many people’s social networks. Finding email correspondents in social networks accurately, though may seem to be straightforward at a first glance, is challenging. Most of the existing online social networking sites recommend possible matches by comparing the information of email accounts and social network profiles, such as display names and email addresses. However, as shown empirically in this paper, such methods may not be effective in practice. To the best of our knowledge, this problem has not been carefully and thoroughly addressed in research. In this paper, we systematically investigate the problem and develop a practical data mining approach. We find that using only the profiles or the graph structures is far from effective. Our method utilizes the similarity between email accounts and social network user profiles, and at the same time explores the similarity between the email communication network and the social network under investigation. We demonstrate the effectiveness of our method using two real data sets on emails and Facebook.     

烟草企业基于Hadoop的数据处理研究

Hadoop是一个开源分布式计算平台。具有高容错性,高伸缩性等优点,允许用户将Hadoop部署在低廉的PC上,充分利用集群的计算和存储能力,完成海量数据的处理。结合国内烟草企业面对不断剧增的业务数据,而现有的业务数据处理能力明显不足的现状,分析烟草企业构建Hadoop分布式数据处理平台的可行性,并详细介绍了Hadoop平台技术及其项目结构和体系结构。