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ALIDA: Intent Discerning Agents for Visual Analytics Interfaces

 

This project is led by the SCIENCE lab at Simon Fraser University and is being done in collaboration with  Purdue PURPL Lab and NanoHub and the Simon Fraser University iVis lab. Intuitive interactive visualizations are designed to scaffold human cognition. But cognition, especially the “higher” processes such as reasoning, tend to be combinatorial and dynamic, and are difficult to standardize. In addtion, there are no operational models of human reasoning, and thus the interface cannot scaffold what is not known or understood. This project focuses on the creation of ALIDA, an autonomous, intelligent agent which uses machine learning and probabilistic models to divine user intent by ascertaining and anticipating the interest and goal behaviors of users in visual analytics interfaces.


Researchers

  • Tera Marie Greensmith
  • Ross Maciejewski, Arizona State University
  • Steve DiPaola

Integrated Science Lab

  • Integrated science methods
    • Pair Analytics
    • Visualization literacy
    • Personal Equation of Interaction
    • Distributed Collaborative Analytics
    • Exploratory Information Seeking
    • ALIDA: Intent discerning agent
    • Financial Planning Decision Processes
  • Health analytics
    • VA for Personalized Medicine
    • VA System to support Health decision-making
    • VA for Flow Cytometry Data Analysis
  • Aircraft Safety & Reliability
  • Emergency Management
  • Public Safety
  • Events
  • Members
  • Research funding
  • Partner organizations (links)
    • UBC Media And Graphics Interdisciplinary Centre (MAGIC)
    • UBC Institute for Computer, Information and Cognitive Systems
    • UNC Charlotte Vis Center
    • VACCINE DHS Center of Excellence
    • Vancouver Institute for Visual Analytics
  • Publications
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Integrated Science Lab                School of Interactive Arts and Technology                 Simon Fraser University