Skip to main content

A Mechanism of Window Switching Prediction Based on User Operation History to Facilitate Multitasking

  • Conference paper
  • First Online:
  • 750 Accesses

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1036))

Abstract

Multitasking on a PC has long been a common practice for users. However, recent rapid technological advancements often complicate multitasking. At this moment, users can utilize many applications on one or more wide displays simultaneously. Thus, the number of tasks and their windows are dramatically increased. Under these circumstances, window switching costs cannot be underestimated. In this paper, we propose a window switching prediction mechanism to facilitate finding the desired window. The mechanism predicts and suggests which window will be needed for the next task based on user operation history. Prediction precision and efficiency of multitasking were investigated by collecting and analysing logs of actual multitasking on subjects’ PCs. The experimental results show that the mechanism was able to reduce the time costs of window switching. We also found that the subjects tended to use both traditional and the proposed window switching methods.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Baeza-Yates, R., Jiang, D.: Predicting the next app that you are going to use. In: Proceedings of the WSDM 2015, pp. 285–294. ACM Press (2015)

    Google Scholar 

  2. Bernstein, M., Shrager, J., Winograd, T.: Taskposé: exploring fluid boundaries in an associative window visualization. In: Proceedings of the UIST 2008, pp. 231–234. ACM Press (2008)

    Google Scholar 

  3. Fitchett, S., Cockburn, A.: AccessRank: predicting what users will do next. In: Proceedings of the CHI 2012, pp. 2239–2242. ACM Press (2012)

    Google Scholar 

  4. Hutchings, D.R., Smith, G., Meyers, B., Czerwinski, M., Robertson, G.: Display space usage and window management operation comparisons between single monitor and multiple monitor users. In: Proceedings of the AVI 2004, pp. 32–39. ACM Press (2004)

    Google Scholar 

  5. Ishak, E.W., Feiner, S.K.: Interacting with hidden content using content-aware free-space transparency. In: Proceedings of the UIST 2004, pp. 189–192. ACM Press (2004)

    Google Scholar 

  6. Lischke, L., Mayer, S., Hoffmann, J., Kratzer, P., Roth, S., Wolf, K., Woniak, P.: Interaction techniques for window management on large high-resolution displays. In: Proceedings of the MUM 2017, pp. 241–247. ACM Press (2017)

    Google Scholar 

  7. Liu, S., Tajima, K.: WildThumb: a web browser supporting efficient task management on wide displays. In: Proceedings of the IUI 2010, pp. 159–168. ACM Press (2010)

    Google Scholar 

  8. Multiple desktops in Windows 10. https://support.microsoft.com/en-us/help/4028538/. Accessed 23 Apr 2019

  9. Oliver, N., Czerwinski, M., Smith, G., Roomp, K.: RelAltTab: assisting users in switching windows. In: Proceedings of the IUI 2008, pp. 385–388. ACM Press (2008)

    Google Scholar 

  10. Standard Banner Sizes List. https://blog.bannersnack.com/banner-standard-sizes/. Accessed 17 Apr 2019

  11. Shibata, H., Omura, K.: Docking window framework: supporting multitasking by docking windows. In: Proceedings of the APCHI 2012, pp. 227–236. ACM Press (2012)

    Google Scholar 

  12. Waldner, M., Steinberger, M., Grasset, R., Schmalstieg, D.: Importance-driven compositing window management. In: Proceedings of the CHI 2011, pp. 959–968. ACM Press (2011)

    Google Scholar 

  13. Warr, A., Chi, E.H., Harris, H., Kuscher, A., Chen, J., Flack, R., Jitkoff, N.: Window shopping: a study of desktop window switching. In: Proceedings of the CHI 2016, pp. 3335–3338. ACM Press (2016)

    Google Scholar 

  14. Xu, Q., Casiez, G.: Push-and-Pull switching: window switching based on window overlapping. In: Proceedings of the CHI 2010, pp. 1335–1338. ACM Press (2010)

    Google Scholar 

  15. Yoshida, K., Ozono, T., Shintani, T.: FoXpace: manipulating windows based on the user’s work history. In: Proceedings of the IIAI-AAI 2016, pp. 698–703. IEEE (2016)

    Google Scholar 

  16. Yoshida, K., Ozono, T., Shintani, T.: Developing an automatic window manipulation system considering content on application windows and user’s behavior. Int. J. Smart Comput. Artif. Intell. 1(2), 59–75 (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Keizo Sato .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Sato, K., Imada, S., Mazume, S., Nakashima, M. (2020). A Mechanism of Window Switching Prediction Based on User Operation History to Facilitate Multitasking. In: Barolli, L., Nishino, H., Enokido, T., Takizawa, M. (eds) Advances in Networked-based Information Systems. NBiS - 2019 2019. Advances in Intelligent Systems and Computing, vol 1036. Springer, Cham. https://doi.org/10.1007/978-3-030-29029-0_15

Download citation

Publish with us

Policies and ethics