Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

4-2013

Abstract

With the popularity of Web 2.0 sites, social networks today increasingly involve different kinds of relationships among different types of users in a single network. Such social networks are said to be multi-dimensional. Analyzing multi-dimensional networks is a challenging research task that requires intelligent visualization techniques. In this paper, we therefore propose a visual analytics tool called ViStruclizer to analyze structures embedded in a multi-dimensional social network. ViStruclizer incorporates structure analyzers that summarize social networks into both node clusters each representing a set of users, and edge clusters representing relationships between users in the node clusters. ViStruclizer supports user interactions to examine specific clusters of users and inter-cluster relationships, as well as to refine the learnt structural summary.

Keywords

Data Mining and Knowledge Discovery, Artificial Intelligence (incl. Robotics), Information Storage and Retrieval

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Publication

Advances in Knowledge Discovery and Data Mining: 17th Pacific-Asia Conference, PAKDD 2013, Gold Coast, Australia, April 14-17, 2013, Proceedings, Part II

Volume

7819

First Page

49

Last Page

60

ISBN

9783642374562

Identifier

10.1007/978-3-642-37456-2_5

Publisher

Springer Verlag

City or Country

Gold Coast, Australia

Additional URL

http:/dx.doi.org/10.1007/978-3-642-37456-2_5

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