检索结果-南通市图书馆

A dynamic influence model of social network hotspot based on grey system

Science China(Information Sciences) 2015年第12期58卷 63-74页

作者： XIAO YunPeng MA Jing LIU YanBing YAN ZhiXian Chongqing University of Posts and Telecommunications (CQUPT) Swiss Federal Institute of Technology (EPFL)

The outbreak of hotspot in social network may contain complex dynamic genesis. Using user behavior data from hotspots in social network, we study how different user groups play different roles for a hotspot topic. Firstly, by analyzing users’ behavior records, we mine group situation that promotes the *** major attributions in a hotspot outbreak, such as individual, peer and group triggers, are defined formally according to the view-point of social identity, social interaction, retweet depth and opinion leader. Secondly,for the problem of the uneven and sparse data in each stage of hotspot topic’s life cycle, we propose a dynamic influence model based on grey system to formalize the effect of different groups. Then the process of hotspot evolution driven by distinct crowd is showed dynamically. The experimental result confirms that the model is able not only to qualify users’ influence on a hotspot topic but also to predict effectively an upcoming change in a hotspot topic.

关键词： social network hotspot topic grey system influence model dynamic evolution

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

A dynamic influence model of social network hotspot based on grey system

引用

Science China Chemistry 2015年第12期58卷 59-70页

作者： XIAO YunPeng MA Jing LIU YanBing YAN ZhiXian Chongqing University of Posts and Telecommunications (CQUPT) Swiss Federal Institute of Technology (EPFL)

The outbreak of hotspot in social network may contain complex dynamic genesis. Using user behavior data from hotspots in social network, we study how different user groups play different roles for a hotspot topic. Firstly, by analyzing users' behavior records, we mine group situation that promotes the *** major attributions in a hotspot outbreak, such as individual, peer and group triggers, are defined formally according to the view-point of social identity, social interaction, retweet depth and opinion leader. Secondly,for the problem of the uneven and sparse data in each stage of hotspot topic's life cycle, we propose a dynamic influence model based on grey system to formalize the effect of different groups. Then the process of hotspot evolution driven by distinct crowd is showed dynamically. The experimental result confirms that the model is able not only to qualify users' influence on a hotspot topic but also to predict effectively an upcoming change in a hotspot topic.

关键词： social network hotspot topic grey system influence model dynamic evolution

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Learning interactions among multi-channel sequences with dynamical influence models

引用

Science China(Information Sciences) 2010年第7期53卷 1336-1344页

作者： ZHANG WeiDong, CHEN Feng & XU WenLi Department of Automation, National Laboratory for Information Science and Technology, Tsinghua University, Beijing 100084, China Department of Automation National Laboratory for Information Science and Technology Tsinghua University Beijing China

Many real applications involve simultaneous recording and analysis of multi-channel information sources. Learning and modeling the interactions among channels is the kernel step to analyze and recognize system characteristics. This paper presents a model that learns the dynamical influence among multi-channel sequences. The model, dynamical influence model, permits functional roles of individual channels to change and models the changing influence strength between channels. By querying the values of influence factors, we can recognize the functional role of each channel qualitatively and learn about to what extent the chains influence each other quantitatively at any time. The experimental results on synthetic data and application of multi-person interaction recognition show that our model is reliable and effective.

关键词： multi-channel processing dynamical interaction influence model activity recognition

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Virtual Network Mapping Through Locality-aware Topological Potential and influence Node Ranking

引用

Chinese Journal of Electronics 2014年第1期23卷 61-64页

作者： ZHANG Dong GAO Long College of Mathematics and Computer Science Fuzhou University

Efficiently mapping multiple independent Virtual networks(VNs) over a common infrastructure substrate is a challenging problem on cloud computing platforms and large-scale future Internet testbeds. Inspired by the idea of data fields, we apply a topological potential function to node ranking and propose an algorithm called Locality-aware node topological potential ranking(LNTPR), which can precisely and efficiently reflect the relative importance of nodes. Using LNTPR and the concept of locality awareness, we develop the Locality-aware influence choosing node(LICN) algorithm based on a node influence model that considers the mutual influence between a mapped node and its candidate mapping *** and LICN improve the integration of node and link mapping. Simulation results demonstrate that the proposed algorithms exhibit good performance in determining revenue, acceptance ratio, and revenue/cost ratio.

关键词： Network virtualization Virtual network Topological potential influence model Locality-aware

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：