273
Views
8
CrossRef citations to date
0
Altmetric
Articles

Multipurpose Public Displays: Can Automated Grouping of Applications and Services Enhance User Experience?

, , , &
Pages 237-249 | Published online: 31 Jan 2014
 

Abstract

Transitioning from bespoke single-purpose displays to multipurpose public interactive displays entails a number of challenges. One challenge is the development of usable mechanisms that allow users to explore the functionality and services on such displays. This article presents a field trial that employs AutoCardSorter, a tool that uses semantic similarity and clustering algorithms, to automatically group the available applications of a public interactive display into categories based on the developer-provided descriptions of each application. The results demonstrate that the grouping generated by AutoCardSorter improved both performance and self-reported usability measures compared to practitioners' existing grouping. In addition, the study investigated the interplay between grouping and interaction modality (i.e., public display vs. desktop). Results tend to support that grouping affects more the user experience with a multipurpose interactive display, but findings were insignificant. This work provides a way for public displays to dynamically update their offered services without sacrificing usability.

Acknowledgments

Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/hihc.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 306.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.