skip to main content
article
Free Access

The vocabulary problem in human-system communication

Authors Info & Claims
Published:01 November 1987Publication History
Skip Abstract Section

Abstract

In almost all computer applications, users must enter correct words for the desired objects or actions. For success without extensive training, or in first-tries for new targets, the system must recognize terms that will be chosen spontaneously. We studied spontaneous word choice for objects in five application-related domains, and found the variability to be surprisingly large. In every case two people favored the same term with probability <0.20. Simulations show how this fundamental property of language limits the success of various design methodologies for vocabulary-driven interaction. For example, the popular approach in which access is via one designer's favorite single word will result in 80-90 percent failure rates in many common situations. An optimal strategy, unlimited aliasing, is derived and shown to be capable of several-fold improvements.

References

  1. 1 Card. S., Moran. T.P. and Newell, A. The Psychology of Hunra~~- Compufer Interaction. Lawrence Erlbaum Associates. Hillsdale. N.J. 1983. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. 2 Dumais. ST., and Landauer. T.K. Describing categories of objects for menu retrieval systems. Brhavior Research Methods. lrrslrunmrts. b Compu~us, 16. 2 (Apr. 1984). 242-248.Google ScholarGoogle Scholar
  3. 3 Furnas. G.W. Experience with an adaptive indexing scheme. Hunla~~ Factors in Computer Sysfenls, CHI '85 Proceedings. Conference held in San Francisco, CA, April 15-18.1985. 131-135. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. 4 Furnas, G.W., Landauer, T.K. Gomez. L.M. and Dumais. ST. Statistical semantics: Analysis of the potential performance of key-word information systems. Bell System Technical /oumal. 62. 6 (Jul.-Aug. 1983). 1753-1806.Google ScholarGoogle Scholar
  5. 5 Gomez. L.M. and Lochbaum, CC. People can retrieve more objects with enriched key-word vocabularies. But is there a human performance cost? In B. Shackel (Ed.) Human-Computer Inleractm- Interact '84, North-Holland. Amsterdam. 257-261.Google ScholarGoogle Scholar
  6. 6 Good, M.D., Whiteside. J.A. Wixon. D. R. and Jones. S.J. Building a user-derived interface. Comn~un. ACM, 27, 10 (Oct. 1984). 1032-1043. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. 7 Herdan. G. Type Tokerr Mathematics: A Textbook of Mathenratical Linguisfics, S-Gravenhage. Mouton. 1960.Google ScholarGoogle Scholar
  8. 8 { Landauer. T.K., Galotti. K. and Hartwell. S. Natural command names and initial learning: A study of text editing terms. Conrntun. ACM, 26, 7 (Jul. 1983). 495-503. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. 9 Reisner. P. Construction of a growing thesaurus by conversational interaction in a man-machine system. Proceedings of the American Dmmw~fafim Insfifute. 26th Annual Meeting. Chicago, Ill. October 1963.Google ScholarGoogle Scholar
  10. 10 Reisner. P. Evaluation of a 'Growing Thesaurus'. Research Paper RC-1662. August 9. 1966. IBM Watson Research Center. Yorktown Heights, N.Y.Google ScholarGoogle Scholar
  11. 11 { Roberts. T.L. and Moran. T.P. The evaluation of text editors: Methodology and empirical results. C~vvn~utt. ACM, 26. 4 (Apr. 1983). 265-283. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. 12 Sparck-Jones. K. A Statistical interpretation of term specificity and its application in retrieval. I. LXX. 28. 1 (Mar. 1972). 11-21.Google ScholarGoogle Scholar
  13. 13 Whalen, T. and Latremouille. S. The effectiveness of a treestructured index when the existence of information is uncertain. Tcledort Behavioral Research 2: The Drsip of Vidrotex Trre Itldiccs. Ottawa, Canada: Department of Communications. (May 1981). pp. 3-12.Google ScholarGoogle Scholar
  14. 14 Zipf, G.K. Hunra~l Behavior wd the Prirmple of Least Effort. AII Irtfnrdurtuw fn Human Emlogy. Addison-Wesley. Reading. Mass. 1949.Google ScholarGoogle Scholar

Index Terms

  1. The vocabulary problem in human-system communication

            Recommendations

            Reviews

            Richard S. Marcus

            .abstract In almost all computer applications, users must enter correct words for the desired objects or actions. For success without extensive training, or in first-tries for new targets, the system must recognize terms that will be chosen spontaneously. We studied spontaneous word choice for objects in five application-related domains, and found the variability suprisingly large. In every case two people favored the same term with probability < 0.20. Simulations show how this fundamental property of language limits the success of various design methodologies for vocabulary-driven interaction. For example the popular approach in which access is via one designers favorite single word will result in 80&#8211;90 percent failure rates in many common situations. An optimal strategy, unlimited aliasing, is derived and shown to be capable of several-fold improvements. &#8212; Authors Abstract This is an excellent paper for anyone interested in interface design where users choice of words is involved, especially those who believe that vocabulary is not a problem. The authors show that a few aliases (synonymous terms) can improve the success of spontaneous selection markedly, and they suggest that unlimited aliasing is the optimum solution. Three approaches to identify good alternate terms are suggested: (1) having a few users supply a &#8220;fair number&#8221; of terms apiece (say, 3&#8211;6); (2) extracting words from the text of descriptions of objects (a la full-text indexing of documents); and (3) adaptively, by noting what new terms users attempt to apply in operation of the system. The authors recognize that there is an imprecision problem, in that one term can be selected by different users to mean different objects. However, they point out that many aliases may be more precise terms than the common terms for which they substitute and thus may actually improve precision. In any case, the authors point out that there are techniques for managing the ambiguities. Their preferred method is interactively to display choices, ordered by frequency of occurence, for the user in order to enable disambiguation. The authors note that effective disambiguation may require good system explanations, which is a problem in itself. The authors also note other possible disambiguation methods (multiterm Boolean expressions, formal query languages, and natural language understanding) but turn away from these as being difficult to implement and not very successful. While I recognize the cogent analysis of much of this paper, I might question the strong emphasis on spontaneous selection. Perhaps some pre-selection mediation by the system (e.g., via menus) could avoid much post-selection disambiguation. More generally, the authors apparent aversion to considering a combination of methods in approaching this problem is questionable, although I recognize that any one of those denigrated by the authors may be inferior to unlimited aliasing as a single solution.

            Access critical reviews of Computing literature here

            Become a reviewer for Computing Reviews.

            Comments

            Login options

            Check if you have access through your login credentials or your institution to get full access on this article.

            Sign in

            Full Access

            • Published in

              cover image Communications of the ACM
              Communications of the ACM  Volume 30, Issue 11
              Nov. 1987
              87 pages
              ISSN:0001-0782
              EISSN:1557-7317
              DOI:10.1145/32206
              Issue’s Table of Contents

              Copyright © 1987 ACM

              Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

              Publisher

              Association for Computing Machinery

              New York, NY, United States

              Publication History

              • Published: 1 November 1987

              Permissions

              Request permissions about this article.

              Request Permissions

              Check for updates

              Qualifiers

              • article

            PDF Format

            View or Download as a PDF file.

            PDF

            eReader

            View online with eReader.

            eReader