The AAAI-11 Workshop on Scalable Integration of Analytics and Visualization
We celebrate the vision of integrating visualization and analytical techniques, enabling computer systems to leverage the abilities of people to perceive and frame problems. Data and model-rich approaches to analytics are becoming more important across many fields of inquiry - and even in delivering value to customers.
Visual analytics problem solving promises to be a natural, collaborative way of allowing people to drive, debug, and apprehend analytical processes, for example machine learning results and experiments. In this workshop, we are looking for examples of and theory supporting the way people and problem solutions can benefit from conversationally-paced, mixed initiative visual analytics. We will focus on interactive exploration of heterogeneous and large-scale data sets, aided by machine learning, data analysis, information fusion, or statistical techniques.
Topics include, but are not restricted to:
- Visualizing and understanding large spaces of symbolic and semantic information.
- Visualization of computational processes from AI and statistics.
- Automation versus interaction for extreme-scale data.
- Degree of personalization for representations and visualizations.
- Visual languages for inputs and outputs of analytical processes.
- Interactive feature selection, transformation, and construction for structuring Bayesian networks.
- Visualization of and interaction with different machine learning algorithms.
- Solving analytical problems using single or multiple representations.
- Integrating visualization and computation with large-scale probabilistic graphical models.
- Handling probabilistic graphical models with hundreds, thousands, or millions of random variables.