On improving application utility prediction

Joshua Hailpern, Nicholas Jitkoff, Joseph Subida, Karrie Karahalios

Research output: Chapter in Book/Report/Conference proceedingConference contribution


When using the computer, each user has some notion that "these applications are important" at a given point in time. We term this subset of applications that the user values as high-utility applications. Identifying these high-utility applications is critical to the fields of Task Analysis, User Interruptions, Workflow Analysis, and Goal Prediction. Yet, existing techniques to identify high-utility applications are based upon task identification, conglomeration of related windows, limited qualitative observation, or common sense. Our work directly associates measurable computer interaction (CPU consumption, window area, etc.) with the user's perceived application utility. In this paper, we present an objective utility function that accurately predicts the user's subjective impressions of application importance. Our work is based upon 321 hours of real-world data from 22 users (both professional and academic) improving existing techniques by over 53%.

Original languageEnglish (US)
Title of host publicationCHI 2010 - The 28th Annual CHI Conference on Human Factors in Computing Systems, Conference Proceedings and Extended Abstracts
Number of pages6
StatePublished - 2010
Event28th Annual CHI Conference on Human Factors in Computing Systems, CHI 2010 - Atlanta, GA, United States
Duration: Apr 10 2010Apr 15 2010

Publication series

NameConference on Human Factors in Computing Systems - Proceedings


Other28th Annual CHI Conference on Human Factors in Computing Systems, CHI 2010
Country/TerritoryUnited States
CityAtlanta, GA


  • Application importance
  • Application utility
  • Modeling

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Graphics and Computer-Aided Design


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