The Community for Technology Leaders
RSS Icon
Subscribe
Zurich, Switzerland
July 4, 2007 to July 6, 2007
ISBN: 0-7695-2907-0
pp: 672-679
Mitchell Beard , Georgetown University
Lise Getoor , University of Maryland
Lisa Singh , Georgetown University
ABSTRACT
Social networks continue to become more and more feature rich. Using local and global structural properties and descriptive attributes are necessary for more sophisticated social network analysis and support for visual mining tasks. While a number of visualization tools for social network applications have been developed, most of them are limited to uni-modal graph representations. Some of the tools support a wide range of visualization options, including interactive views. Others have better support for calculating structural graph properties such as the density of the graph or deploying traditional statistical social network analysis. We present Invenio, a new tool for visual mining of socials. Invenio integrates a wide range of interactive visualization options from Prefuse, with graph mining algorithm support from JUNG. While the integration expands the breadth of functionality within the core engine of the tool, our goal is to interactively explore multi-modal, multi-relational social networks. Invenio also supports construction of views using both database operations and basic graph mining operations.
INDEX TERMS
null
CITATION
Mitchell Beard, Lise Getoor, Lisa Singh, "Visual Mining of Multi-Modal Social Networks at Different Abstraction Levels", IV, 2007, 2013 17th International Conference on Information Visualisation, 2013 17th International Conference on Information Visualisation 2007, pp. 672-679, doi:10.1109/IV.2007.126
25 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool