7. Conclusions
This paper makes two main contributions. First, it presents a study of
the impact of three user interface components on the time to enter
information into a computer: handwriting recognition, adaptive menus,
and predictive fillin. Handwriting recognition is slower than typing
but is preferred by users. Advances in handwriting recognition may
make it faster, but recognition would still be much slower than
choosing a value from a menu or predictive fillin. All three
components work well together and are preferred by users.
Second, this paper discusses principles for applying adaptive menus
and predictive fillin to new application areas. Fields with a few,
frequently repeated values are candidates for adaptive menus;
functional dependencies indicate candidates for predictive
fillin. Whether these characteristics can be learned at run-time is a
topic for future research.
Acknowledgments
Kerry Hersh Raghavendra provided the names used in
Section 4.
Apple
Computer developed and supports Newton and the Newton ToolKit
programming environment. The Newton AI group at WSU provided many
useful comments on an earlier draft of this paper. Geoff Allen, Karl
Hakimian, Mike Kibler, and the EECS staff provided a consistent and
reliable computing environment. Anonymous reviewers of an earlier
draft of this paper provided many (many) valuable suggestions. This
work was supported in part by NASA under grant number NCC 2-794.
References
- Agre, P. E., & Chapman, D. (1987). Pengi: An implementation of a
theory of activity. Proceedings of the Sixth National Conference on
Artificial Intelligence (pp. 268-272). Seattle, WA: AAAI Press.
- Cesar, M., & Shinghal, R. (1990). An algorithm for segmenting
handwriting postal codes. Int. J. Man-Machine Studies,
33, 63-80.
- Culbert, M. (1994). Low power hardware for a high performance
PDA. Proceedings of the 1994 IEEE Computer Conference. San Francisco,
CA: IEEE.
- Dent, L., Boticario, J., McDermott, J., Mitchell, T., & Zabowski,
D. (1992). A personal learning apprentice. Proceedings of the Tenth
National Conference on Artificial Intelligence (pp. 96-103). San Jose,
CA: AAAI Press.
- Hermens, L. A., & Schlimmer, J. C. (1994). A machine learning
apprentice for the completion of repetitive forms. IEEE
Expert, 9, 1, 28-33.
- Horswill, I. D., & Brooks, R. A. (1988). Situated vision in a
dynamic world: Chasing objects. Proceedings of the Seventh National
Conference on Artificial Intelligence (pp. 796-800). St. Paul, MN:
AAAI Press.
- Kolodner, J. (1993). Case-based reasoning. San Francisco, CA:
Morgan Kaufmann.
- Kreigh, R. J., Pesot, J. F., & Halcomb, C. G. (1990). An
evaluation of look-ahead help fields on various types of menu
hierarchies. Int. J. Man-Machine Studies, 32, 649-661.
- Lee, J. (1990). Intelligent interfaces and UIMS. In D. A. Duce,
M. R. Gomes, F. R. A. Hopgood, & J. R. Lee (Eds.), User interface
management and design. NY: Springer-Verlag.
- MacKenzie, S. I., Nonnecke, B., Riddersma, S., McQueen, C., &
Meltz, M. (1994). Alphanumeric entry on pen-based
computers. Int. J. of Human-Computer Studies, 41, 755-792.
- Meyer, A. (1995). Pen computing: A technology overview and a
vision. SIGCHI Bulletin, 27, 3, 46-90.
- Mitchell, J., & Shneiderman, B. (1989). Dynamic versus static
menus: An exploratory comparison. SIGCHI Bulletin,
20, 4, 33-37.
- Norman, K. L. (1991). The psychology of menu selection: Designing
cognitive control of the human/computer interface. Norwood, NJ: Ablex.
- Pomerleau, D. A. (1995). A connectionist technique for accelerated
textual input: Letting a network do the typing. In Advances in Neural
Information Processing Systems 7. Cambridge, MA: MIT Press.
- Rissland, E. L. (1984). Ingredients of intelligent user
interfaces. Int. J. Man-Machine Studies, 21, 377-388.
- Raju, K. V. S. V. N., & Majumdar, A. K. (1988). Fuzzy functional
dependencies and lossless join decomposition of fuzzy relational
database systems. ACM Trans. Database Syst. 13,
2, 129-166.
- Russell, S. J. (1989). The use of knowledge in analogy and
induction. San Francisco, CA: Morgan Kaufmann.
- Schlimmer, J. C., & Hermens, L. A. (1993). Software agents:
Completing patterns and constructing interfaces. Journal of Artificial
Intelligence Research, 1, 61-89.
- Sears, A. & Shneiderman, B. (1994). Split menus: Effectively using
selection frequency to organize menus. ACM Trans. on Computer-Human
Interaction, 1, 1, 27-51.
- Smith, W. R. (1994). The Newton application
architecture. Proceedings of the 1994 IEEE Computer Conference. San
Francisco, CA: IEEE.
- Snowberry, K., Parkinson, S., & Sisson, N. (1985). Effects of help
fields on navigating through hierarchical menu
structures. Int. J. Man-Machine Studies, 22, 479-491.
- Ullman, J. D. (1988). Principles of database and knowledge-base
systems: Volume 1. Rockville, MD: Computer Science Press.
- Ward, J. R., & Blesser, B. (1986). Interactive recognition of
handprinted characters for computer input. SIGCHI Bulletin,
18, 1, 44-57.
- Wilkinson, L., Hill, M., & Vang, E. (1992). SYSTAT: Graphics,
Version 5.2 Edition. Evanston, IL: SYSTAT, Inc.
- Witten, I. H., Cleary, J. G., & Greenberg, S. (1984). On
frequency-based menu-splitting algorithms. Int. J. Man-Machine
Studies, 21, 135-148.
- Yoshida, K. (1994). User command prediction by graph-based
induction. Sixth IEEE International Conference on Tools with
Artificial Intelligence (pp. 732-735). New Orleans, LA: IEEE.
- Ziarko, W. (1992). The discovery, analysis, and representation of
data dependencies. In Piatetsky-Shapiro, G., & Frawley, W. (Eds.),
Knowledge discovery in databases. Palo Alto, CA: AAAI Press.
Jeffrey C. Schlimmer,
schlimme@eecs.wsu.edu,
5 December 1994