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通过语义和结构抽象对大型异构社交网络进行可视化分析。

Visual analysis of large heterogeneous social networks by semantic and structural abstraction.

作者信息

Shen Zeqian, Ma Kwan-Liu, Eliassi-Rad Tina

机构信息

Department of Computer Science, University of California at Davis, 95616, USA.

出版信息

IEEE Trans Vis Comput Graph. 2006 Nov-Dec;12(6):1427-39. doi: 10.1109/TVCG.2006.107.


DOI:10.1109/TVCG.2006.107
PMID:17073366
Abstract

Social network analysis is an active area of study beyond sociology. It uncovers the invisible relationships between actors in a network and provides understanding of social processes and behaviors. It has become an important technique in a variety of application areas such as the Web, organizational studies, and homeland security. This paper presents a visual analytics tool, OntoVis, for understanding large, heterogeneous social networks, in which nodes and links could represent different concepts and relations, respectively. These concepts and relations are related through an ontology (also known as a schema). OntoVis is named such because it uses information in the ontology associated with a social network to semantically prune a large, heterogeneous network. In addition to semantic abstraction, OntoVis also allows users to do structural abstraction and importance filtering to make large networks manageable and to facilitate analytic reasoning. All these unique capabilities of OntoVis are illustrated with several case studies.

摘要

社会网络分析是社会学之外一个活跃的研究领域。它揭示了网络中参与者之间无形的关系,并有助于理解社会过程和行为。它已成为网络、组织研究和国土安全等各种应用领域的一项重要技术。本文提出了一种可视化分析工具OntoVis,用于理解大型异构社会网络,其中节点和链接可分别表示不同的概念和关系。这些概念和关系通过本体(也称为模式)相关联。OntoVis之所以这样命名,是因为它使用与社会网络相关联的本体中的信息对大型异构网络进行语义修剪。除了语义抽象之外,OntoVis还允许用户进行结构抽象和重要性过滤,以使大型网络易于管理并便于进行分析推理。OntoVis的所有这些独特功能都通过几个案例研究进行了说明。

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