Type of Document Dissertation Author Endert, Alex Author's Email Address firstname.lastname@example.org URN etd-07112012-123927 Title Semantic Interaction for Visual Analytics: Inferring Analytical Reasoning for Model Steering Degree PhD Department Computer Science and Applications Advisory Committee
Advisor Name Title North, Christopher L. Committee Chair Bowman, Douglas A. Committee Member Leman, Scotland C. Committee Member May, Richard Committee Member Quek, Francis K. H. Committee Member Keywords
- user interaction
- visual analytics
- model steering
Date of Defense 2012-07-10 Availability unrestricted AbstractUser interaction in visual analytic systems is critical to enabling visual data exploration. Through interacting with visualizations, users engage in sensemaking, a process of developing and understanding relationships within datasets through foraging and synthesis. For example, two-dimensional layouts of high-dimensional data can be generated by dimension reduction models, and provide users with an overview of the relationships between information. However, exploring such spatializations can require expertise with the internal mechanisms and parameters of these models.
The core contribution of this work is semantic interaction, capable of steering such models without requiring expertise in dimension reduction models, but instead leveraging the domain expertise of the user. Semantic interaction infers the analytical reasoning of the user with model updates, steering the dimension reduction model for visual data exploration. As such, it is an approach to user interaction that leverages interactions designed for synthesis, and couples them with the underlying mathematical model to provide computational support for foraging. As a result, semantic interaction performs incremental model learning to enable synergy between the user’s insights and the mathematical model. The contributions of this work are organized by providing a description of the principles of semantic interaction, providing design guidelines through the development of a visual analytic prototype, ForceSPIRE, and the evaluation of the impact of semantic interaction on the analytic process. The positive results of semantic interaction open a fundamentally new design space for designing user interactions in visual analytic systems.
This research was funded in part by the National Science Foundation, CCF-0937071 and CCF-0937133, the Institute for Critical Technology and Applied Science at Virginia Tech, and the National Geospatial-Intelligence Agency contract #HMI1582-05-1-2001.
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