@article {17238,
	title = {Integrating Statistics and Visualization for Exploratory Power: From Long-Term Case Studies to Design Guidelines},
	journal = {IEEE Computer Graphics and Applications},
	volume = {29},
	year = {2009},
	month = {2009/06//May},
	pages = {39 - 51},
	abstract = {Evaluating visual-analytics systems is challenging because laboratory-based controlled experiments might not effectively represent analytical tasks. One such system, Social Action, integrates statistics and visualization in an interactive exploratory tool for social network analysis. This article describes results from long-term case studies with domain experts and extends established design goals for information visualization.},
	keywords = {case studies, Control systems, Data analysis, data mining, data visualisation, Data visualization, data-mining, design guidelines, Employment, exploration, Filters, Guidelines, Information Visualization, insights, laboratory-based controlled experiments, Performance analysis, social network analysis, Social network services, social networking (online), social networks, SocialAction, statistical analysis, Statistics, visual analytics, visual-analytics systems, Visualization},
	isbn = {0272-1716},
	doi = {10.1109/MCG.2009.44},
	author = {Perer,A. and Shneiderman, Ben}
}
@article {17397,
	title = {Temporal Summaries: Supporting Temporal Categorical Searching, Aggregation and Comparison},
	journal = {IEEE Transactions on Visualization and Computer Graphics},
	volume = {15},
	year = {2009},
	month = {2009/12//Nov},
	pages = {1049 - 1056},
	abstract = {When analyzing thousands of event histories, analysts often want to see the events as an aggregate to detect insights and generate new hypotheses about the data. An analysis tool must emphasize both the prevalence and the temporal ordering of these events. Additionally, the analysis tool must also support flexible comparisons to allow analysts to gather visual evidence. In a previous work, we introduced align, rank, and filter (ARF) to accentuate temporal ordering. In this paper, we present temporal summaries, an interactive visualization technique that highlights the prevalence of event occurrences. Temporal summaries dynamically aggregate events in multiple granularities (year, month, week, day, hour, etc.) for the purpose of spotting trends over time and comparing several groups of records. They provide affordances for analysts to perform temporal range filters. We demonstrate the applicability of this approach in two extensive case studies with analysts who applied temporal summaries to search, filter, and look for patterns in electronic health records and academic records.},
	keywords = {Aggregates, Collaborative work, Computational Biology, Computer Graphics, Data analysis, data visualisation, Data visualization, Databases, Factual, Displays, Event detection, Filters, Heparin, History, Human computer interaction, Human-computer interaction, HUMANS, Information Visualization, Interaction design, interactive visualization technique, Medical Records Systems, Computerized, Pattern Recognition, Automated, Performance analysis, Springs, temporal categorical data visualization, temporal categorical searching, temporal ordering, temporal summaries, Thrombocytopenia, Time factors},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2009.187},
	author = {Wang,T. D and Plaisant, Catherine and Shneiderman, Ben and Spring, Neil and Roseman,D. and Marchand,G. and Mukherjee,V. and Smith,M.}
}
@article {16983,
	title = {Balancing Systematic and Flexible Exploration of Social Networks},
	journal = {IEEE Transactions on Visualization and Computer Graphics},
	volume = {12},
	year = {2006},
	month = {2006/10//Sept},
	pages = {693 - 700},
	abstract = {Social network analysis (SNA) has emerged as a powerful method for understanding the importance of relationships in networks. However, interactive exploration of networks is currently challenging because: (1) it is difficult to find patterns and comprehend the structure of networks with many nodes and links, and (2) current systems are often a medley of statistical methods and overwhelming visual output which leaves many analysts uncertain about how to explore in an orderly manner. This results in exploration that is largely opportunistic. Our contributions are techniques to help structural analysts understand social networks more effectively. We present SocialAction, a system that uses attribute ranking and coordinated views to help users systematically examine numerous SNA measures. Users can (1) flexibly iterate through visualizations of measures to gain an overview, filter nodes, and find outliers, (2) aggregate networks using link structure, find cohesive subgroups, and focus on communities of interest, and (3) untangle networks by viewing different link types separately, or find patterns across different link types using a matrix overview. For each operation, a stable node layout is maintained in the network visualization so users can make comparisons. SocialAction offers analysts a strategy beyond opportunism, as it provides systematic, yet flexible, techniques for exploring social networks},
	keywords = {Aggregates, algorithms, attribute ranking, Cluster Analysis, Computer Graphics, Computer simulation, Coordinate measuring machines, coordinated views, Data analysis, data visualisation, Data visualization, exploratory data analysis, Filters, Gain measurement, graph theory, Graphical user interfaces, Information Storage and Retrieval, interactive graph visualization, matrix algebra, matrix overview, Models, Biological, Navigation, network visualization, Pattern analysis, Population Dynamics, Social Behavior, social network analysis, Social network services, social networks, social sciences computing, Social Support, SocialAction, software, statistical analysis, statistical methods, User-Computer Interface},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2006.122},
	author = {Perer,A. and Shneiderman, Ben}
}
@article {17307,
	title = {Network Visualization by Semantic Substrates},
	journal = {IEEE Transactions on Visualization and Computer Graphics},
	volume = {12},
	year = {2006},
	month = {2006/10//Sept},
	pages = {733 - 740},
	abstract = {Networks have remained a challenge for information visualization designers because of the complex issues of node and link layout coupled with the rich set of tasks that users present. This paper offers a strategy based on two principles: (1) layouts are based on user-defined semantic substrates, which are non-overlapping regions in which node placement is based on node attributes, (2) users interactively adjust sliders to control link visibility to limit clutter and thus ensure comprehensibility of source and destination. Scalability is further facilitated by user control of which nodes are visible. We illustrate our semantic substrates approach as implemented in NVSS 1.0 with legal precedent data for up to 1122 court cases in three regions with 7645 legal citations},
	keywords = {Automatic control, data visualisation, Data visualization, Displays, Filters, Graphical user interfaces, Information Visualization, information visualization designers, Law, legal citations, Legal factors, legal precedent data, network visualization, NVSS 1.0, scalability, semantic substrate, Terminology, Tunneling, user-defined semantic substrates},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2006.166},
	author = {Shneiderman, Ben and Aris,A.}
}
@conference {19649,
	title = {A Rao-Blackwellized particle filter for EigenTracking},
	booktitle = {Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004},
	volume = {2},
	year = {2004},
	month = {2004/06//},
	pages = {II - 980-II-986 Vol.2},
	abstract = {Subspace representations have been a popular way to model appearance in computer vision. In Jepson and Black{\textquoteright}s influential paper on EigenTracking, they were successfully applied in tracking. For noisy targets, optimization-based algorithms (including EigenTracking) often fail catastrophically after losing track. Particle filters have recently emerged as a robust method for tracking in the presence of multi-modal distributions. To use subspace representations in a particle filter, the number of samples increases exponentially as the state vector includes the subspace coefficients. We introduce an efficient method for using subspace representations in a particle filter by applying Rao-Blackwellization to integrate out the subspace coefficients in the state vector. Fewer samples are needed since part of the posterior over the state vector is analytically calculated. We use probabilistic principal component analysis to obtain analytically tractable integrals. We show experimental results in a scenario in which we track a target in clutter.},
	keywords = {analytically tractable integrals, Computer vision, EigenTracking, Filters, Gaussian processes, modal analysis, multi-modal distributions, NOISE, noisy targets, optimisation, optimization-based algorithms, Particle filters, Particle measurements, Particle tracking, Principal component analysis, probabilistic principal component analysis, Rao-Blackwellized particle filter, Robustness, SHAPE, State estimation, state vector, subspace coefficients, Subspace representations, target tracking, vectors},
	author = {Zia Khan and Balch, T. and Dellaert, F.}
}
@conference {17498,
	title = {Visualization methods for personal photo collections: browsing and searching in the PhotoFinder},
	booktitle = {2000 IEEE International Conference on Multimedia and Expo, 2000. ICME 2000},
	volume = {3},
	year = {2000},
	month = {2000///},
	pages = {1539-1542 vol.3 - 1539-1542 vol.3},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Software tools for personal photo collection management are proliferating, but they usually have limited searching and browsing functions. We implemented the PhotoFinder prototype to enable non-technical users of personal photo collections to search and browse easily. PhotoFinder provides a set of visual Boolean query interfaces, coupled with dynamic query and query preview features. It gives users powerful search capabilities. Using a scatter plot thumbnail display and drag-and-drop interface, PhotoFinder is designed to be easy to use for searching and browsing photos},
	keywords = {Browsing, Computer science, digital photo library, Displays, drag-and-drop interface, dynamic query, Educational institutions, Filters, Histograms, Image retrieval, personal computing, personal photo collections, photo collection management, PhotoFinder, Prototypes, query preview, scatter plot thumbnail display, Scattering, searching, software libraries, software tools, User interfaces, visual Boolean query interfaces, visual databases, Visualization, visualization methods},
	isbn = {0-7803-6536-4},
	doi = {10.1109/ICME.2000.871061},
	author = {Kang,Hyunmo and Shneiderman, Ben}
}
