@conference {14405,
	title = {Visual Mining of Multi-Modal Social Networks at Different Abstraction Levels},
	booktitle = {Information Visualization, 2007. IV {\textquoteright}07. 11th International Conference},
	year = {2007},
	month = {2007/07//},
	pages = {672 - 679},
	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.},
	keywords = {computing;, database;interactive, graph, management, mining;data, network;structural, property;visual, sciences, social, systems;graph, systems;social, theory;interactive, visualisation;database, visualization;multimodal},
	doi = {10.1109/IV.2007.126},
	author = {Singh,L. and Beard,M. and Getoor, Lise and Blake,M.B.}
}
@conference {14498,
	title = {D-Dupe: An Interactive Tool for Entity Resolution in Social Networks},
	booktitle = {Visual Analytics Science And Technology, 2006 IEEE Symposium On},
	year = {2006},
	month = {2006/11/31/2},
	pages = {43 - 50},
	abstract = {Visualizing and analyzing social networks is a challenging problem that has been receiving growing attention. An important first step, before analysis can begin, is ensuring that the data is accurate. A common data quality problem is that the data may inadvertently contain several distinct references to the same underlying entity; the process of reconciling these references is called entity-resolution. D-Dupe is an interactive tool that combines data mining algorithms for entity resolution with a task-specific network visualization. Users cope with complexity of cleaning large networks by focusing on a small subnetwork containing a potential duplicate pair. The subnetwork highlights relationships in the social network, making the common relationships easy to visually identify. D-Dupe users resolve ambiguities either by merging nodes or by marking them distinct. The entity resolution process is iterative: as pairs of nodes are resolved, additional duplicates may be revealed; therefore, resolution decisions are often chained together. We give examples of how users can flexibly apply sequences of actions to produce a high quality entity resolution result. We illustrate and evaluate the benefits of D-Dupe on three bibliographic collections. Two of the datasets had already been cleaned, and therefore should not have contained duplicates; despite this fact, many duplicates were rapidly identified using D-Dupe{\textquoteright}s unique combination of entity resolution algorithms within a task-specific visual interface},
	keywords = {algorithm;data, analysis;social, computing;user, D-Dupe, interactive, interface;data, interfaces;, mining, mining;interactive, network, problem;entity, QUALITY, resolution;entity-resolution;social, sciences, systems;social, tool;data, visual, visualization;task-specific},
	doi = {10.1109/VAST.2006.261429},
	author = {Bilgic,M. and Licamele,L. and Getoor, Lise and Shneiderman, Ben}
}
