Toward User-Adaptive Visualizations

Speaker:  Cristina Conati – Vancouver, BC, Canada
Topic(s):  Artificial Intelligence, Machine Learning, Computer Vision, Natural language processing

Abstract

As digital information continues to accumulate in our lives, information visualizations have become an increasingly relevant tool for discovering trends and shaping stories from this overabundance of data.   Visualizations are typically designed based on the data to be displayed and the tasks to be supported, but they follow a one-size-fits-all approach when it comes to user individual differences such as expertise, cognitive abilities, states and preferences. There is, however,  mounting evidence that these user characteristics can significantly influence user experience during information visualization tasks. These findings have triggered research on user-adaptive visualizations, i.e. visualizations that can track and adapt to relevant user characteristics and specific needs.
 
In this talk, Cristina will present results on which user individual differences can impact visualization processing and on how these differences can be captured using predictive models based on eye-tracking data. She will also discuss how  to leverage these models to provide personalized support that can improve the user’s experience with a visualization.

About this Lecture

Number of Slides:  40
Duration:  45 minutes
Languages Available:  English, Italian
Last Updated: 

Request this Lecture

To request this particular lecture, please complete this online form.

Request a Tour

To request a tour with this speaker, please complete this online form.

All requests will be sent to ACM headquarters for review.