Graph drawing by force-directed placement
Software—Practice & Experience
Visualization of a document collection: the vibe system
Information Processing and Management: an International Journal
VIKI: spatial hypertext supporting emergent structure
ECHT '94 Proceedings of the 1994 ACM European conference on Hypermedia technology
Computer Supported Cooperative Work
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CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
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Dust & magnet: multivariate information visualization using a magnet metaphor
Information Visualization
VisTrails: visualization meets data management
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Glass box: capturing, archiving, and retrieving workstation activities
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Supporting the analytical reasoning process in information visualization
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Evaluating Visual Analytics at the 2007 VAST Symposium Contest
IEEE Computer Graphics and Applications
Graphical Histories for Visualization: Supporting Analysis, Communication, and Evaluation
IEEE Transactions on Visualization and Computer Graphics
Recovering Reasoning Processes from User Interactions
IEEE Computer Graphics and Applications
Space to think: large high-resolution displays for sensemaking
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
STREAMIT: Dynamic visualization and interactive exploration of text streams
PACIFICVIS '11 Proceedings of the 2011 IEEE Pacific Visualization Symposium
A cartographic approach to visualizing conference abstracts
IEEE Computer Graphics and Applications
iPCA: an interactive system for PCA-based visual analytics
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
Designing large high-resolution display workspaces
Proceedings of the International Working Conference on Advanced Visual Interfaces
The semantics of clustering: analysis of user-generated spatializations of text documents
Proceedings of the International Working Conference on Advanced Visual Interfaces
Interaction junk: user interaction-based evaluation of visual analytic systems
Proceedings of the 2012 BELIV Workshop: Beyond Time and Errors - Novel Evaluation Methods for Visualization
POWERWALL: int. workshop on interactive, ultra-high-resolution displays
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Crowd synthesis: extracting categories and clusters from complex data
Proceedings of the 17th ACM conference on Computer supported cooperative work & social computing
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Visual analytics emphasizes sensemaking of large, complex datasets through interactively exploring visualizations generated by statistical models. For example, dimensionality reduction methods use various similarity metrics to visualize textual document collections in a spatial metaphor, where similarities between documents are approximately represented through their relative spatial distances to each other in a 2D layout. This metaphor is designed to mimic analysts' mental models of the document collection and support their analytic processes, such as clustering similar documents together. However, in current methods, users must interact with such visualizations using controls external to the visual metaphor, such as sliders, menus, or text fields, to directly control underlying model parameters that they do not understand and that do not relate to their analytic process occurring within the visual metaphor. In this paper, we present the opportunity for a new design space for visual analytic interaction, called semantic interaction, which seeks to enable analysts to spatially interact with such models directly within the visual metaphor using interactions that derive from their analytic process, such as searching, highlighting, annotating, and repositioning documents. Further, we demonstrate how semantic interactions can be implemented using machine learning techniques in a visual analytic tool, called ForceSPIRE, for interactive analysis of textual data within a spatial visualization. Analysts can express their expert domain knowledge about the documents by simply moving them, which guides the underlying model to improve the overall layout, taking the user's feedback into account.