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On improving application utility prediction

Published: 10 April 2010 Publication History

Abstract

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%.

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    cover image ACM Conferences
    CHI EA '10: CHI '10 Extended Abstracts on Human Factors in Computing Systems
    April 2010
    2219 pages
    ISBN:9781605589305
    DOI:10.1145/1753846

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    New York, NY, United States

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    Published: 10 April 2010

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    Author Tags

    1. application importance
    2. application utility
    3. modeling

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    CHI EA '10 Paper Acceptance Rate 350 of 1,346 submissions, 26%;
    Overall Acceptance Rate 6,164 of 23,696 submissions, 26%

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