Quantitative results comparing three intelligent interfaces for information capture: a case study adding name information into an electronic personal organizer

  • Authors:
  • Jeffrey C. Schlimmer;Patricia Crane Wells

  • Affiliations:
  • School of Electrical Engineering & Computer Science, Washington State University, Pullman, WA;AllPen Software, Inc., Los Gatos, CA

  • Venue:
  • Journal of Artificial Intelligence Research
  • Year:
  • 1996

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Abstract

Efficiently entering information into a computer is key to enjoying the benefits of computing. This paper describes three intelligent user interfaces: handwriting recognition, adaptive menus, and predictive fillin. In the context of adding a person's name and address to an electronic organizer, tests show handwriting recognition is slower than typing on an on-screen, soft keyboard, while adaptive menus and predictive fillin can be twice as fast. This paper also presents strategies for applying these three interfaces to other information collection domains.