University of Illinois Urbana-Champaign

Understanding and Developing Models for Detecting and Differentiating Breakpoints during Task Execution

Iqbal, Shamsi T.; Bailey, Brian P.

Content Files
Understanding and Developing Models for Detecting and Differentiating Breakpoints during Task Execution.pdf

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https://hdl.handle.net/2142/11263

Description

Title
Understanding and Developing Models for Detecting and Differentiating Breakpoints during Task Execution
Author(s)
  • Iqbal, Shamsi T.
  • Bailey, Brian P.
Issue Date
2006-10
Keyword(s)
computer science
Date of Ingest
2009-04-21T19:05:30Z
Abstract
The ability to detect and differentiate breakpoints during task execution is critical for enabling defer-to-breakpoint policies within interruption management. In this work, we examine the feasibility of building models that are capable of detecting and differentiating three granularities (types) of perceptually meaningful breakpoints, without specifications of users. tasks. We collected an ecological sample of task execution data, and then asked human observers to review the collected videos and identify perceived breakpoints and their type. Statistical methods were applied to learn models that map features of the ongoing interaction to each type of breakpoint. Results showed that the models were able to detect and differentiate breakpoints with reasonably high accuracy across tasks. Among many uses, such models can enable interruption management systems to better realize defer-to-breakpoint policies for interactive, free-form tasks.
Type of Resource
text
Genre of Resource
Technical Report
Permalink
http://hdl.handle.net/2142/11263
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