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BEHACOM - a dataset modelling users' behaviour in computers.

Pedro M Sánchez Sánchez1, José M Jorquera Valero1, Mattia Zago1

  • 1Department of Information Engineering and Communications, University of Murcia, Murcia 30100 Spain.

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|June 11, 2020
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Summary
This summary is machine-generated.

This study introduces the BEHACOM dataset, capturing user computer interactions over 55 days. The privacy-preserving dataset models resource usage and application activities for behavioral analysis.

Keywords:
Behavioural datasetapplication statisticscomputerkeyboard activitymouse movementsresource usage

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Area of Science:

  • Computer Science
  • Human-Computer Interaction
  • Data Science

Background:

  • Understanding user computer interaction is crucial for system optimization and personalized computing.
  • Existing datasets often lack comprehensive, long-term behavioral data or robust privacy measures.

Purpose of the Study:

  • To introduce and describe the BEHACOM dataset, a novel collection of user computer interaction data.
  • To detail the methodology for collecting and processing privacy-preserving behavioral data.
  • To provide a foundation for research in user behavior modeling and computer system analysis.

Main Methods:

  • Collected computer interaction data from twelve users over 55 consecutive days.
  • Modeled user behavior using one-minute time windows, capturing CPU, memory, application, mouse, and keyboard activities.
  • Implemented privacy-preserving techniques throughout data collection and analysis.

Main Results:

  • The BEHACOM dataset comprises detailed, time-windowed features of computer resource utilization and user activities.
  • The dataset includes explanations of features and the software used for data acquisition and processing.
  • Data distribution characteristics of the BEHACOM dataset are described.

Conclusions:

  • The BEHACOM dataset offers a valuable resource for studying naturalistic computer user behavior.
  • The privacy-preserving methodology ensures ethical data utilization for research.
  • This dataset can advance research in areas like adaptive interfaces, security, and user modeling.