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Mobile Sensing for Task Engagement Inference

Gašper Urh (2016) Mobile Sensing for Task Engagement Inference. MSc thesis.

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    Smartphones have become very powerful and personal devices, but still have to live up to their potential. To date, we have no automated means of uncovering a user's task engagement, which would be beneficial in numerous areas -- from mobile applications to human resource management systems. In this thesis, we explore the possibility of automated task engagement inference using smartphone sensors. We try to find an answer by developing a data collection system based on a mobile application. We deploy and distribute the app among volunteers to collect data on our server. We then use machine learning approaches on collected data to uncover a weak link between task engagement and smartphone usage data and find out that the collected data is highly personalized.

    Item Type: Thesis (MSc thesis)
    Keywords: smartphone, mobile sensing, machine learning, task engagement
    Number of Pages: 61
    Language of Content: English
    Mentor / Comentors:
    Name and SurnameIDFunction
    doc. dr. Veljko PejovićMentor
    Link to COBISS: http://www.cobiss.si/scripts/cobiss?command=search&base=51012&select=(ID=1537279427)
    Institution: University of Ljubljana
    Department: Faculty of Computer and Information Science
    Item ID: 3648
    Date Deposited: 18 Oct 2016 14:55
    Last Modified: 15 Nov 2016 09:21
    URI: http://eprints.fri.uni-lj.si/id/eprint/3648

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