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Acquiring user models

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Abstract

Existing machine techniques for acquiring user models are characterized along five orthogonal dimensions: passive/active, user-initiated/automatic, logical/plausible, direct/indirect, and on-line/off-line. Passive techniques observe users whereas active techniques query users. User-initiated techniques require that users volunteer information; automatic techniques do not. The logical/plausible dimension measures the accuracy of derived user model data. Indirect techniques build upon data gathered by more direct methods. On-line techniques acquire user models in real-time during user interaction, while off-line techniques work after the user interaction is finished. Commonalities and differences in capabilities and features of different user model acquisition techniques are analyzed along the above dimensions, and the relationship of these techniques to similar techniques in other areas of artificial intelligence are discussed.

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References

  • Allen, J. F. and Perrault, C. R. (1980). Analyzing Intention in Utterances.Artificial Intelligence 15, 143–178.

    Google Scholar 

  • Allgayer, J., Ohlbach, H. J. and Reddig, C. (1992). Modelling Agents with Logic. In André, E., Cohen, R., Graf, W., Kass, B., Paris, C. and Wahlster, W. (Eds.),Proceedings of UM92, Third International Workshop on User Modeling, pp. 22–34. Available as DFKI Document D-92-17, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Stulsatzenhasweg 3, D-6600 Saarbrücken 11, FRG.

    Google Scholar 

  • Appelt, D. E. and Pollack, M. E. (1992). Weighted Abduction for Plan Ascription.User Modeling and User-Adapted Interaction 2(1–2), 1–25.

    Google Scholar 

  • Bobrow, D. G., Kaplan, R. M., Kay, M., Norman, D. A., Thompson, H. and Winograd, T. (1977). GUS-1, a Frame-Driven Dialog System.Artificial Intelligence 8(2), 155–173.

    Google Scholar 

  • Brajnik, G. and Tasso, C. (1992) A Flexible Tool for Developing User Model Applications with Nonmonotonic Reasoning Capabilities. In André, E., Cohen, R., Graf, W., Kass, B., Paris, C. and Wahlster, W. (Eds.),Proceedings of UM92, Third International Workshop on User Modeling, pp. 42–63. Available as DFKI Document D-92-17, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Stulsatzenhasweg, 3, D-6600 Saarbrücken 11, FRG.

    Google Scholar 

  • Bunt, H. C. (1989). Modular Incremental Modelling of Belief and Intention, In theProceedings of the Second International Workshop on User Modelling, Honolulu, HI.

  • Burton, R. R. (1982). Diagnosing Bugs in a Simple Procedural Skill. In Sleeman, D. H. and Brown, J. S. (Eds.),Intelligent Tutoring Systems. Academic Press, New York, pp. 157–183.

    Google Scholar 

  • Carberry, S. (1990). Incorporating Default Inferences into Plan Recognition. In theEighth National Conference on Artificial Intelligence, Boston, pp. 471–478.

  • Charniak, E. (1983). The Bayesian Basis of Commonsense Medical Diagnosis. In theThird National Conference on Artificial Intelligence, Washington, DC, pp. 70–73.

  • Chin, D. N. (1987).Intelligent agents as a basis for natural language interfaces. Ph.D. thesis, University of California, Berkeley. Also available as Computer Science Division, University of California, Berkeley, Report No. UCB/CSD 88/396.

    Google Scholar 

  • Chin, D. N. (1989). KNOME: Modeling What the User Knows in UC. In Kobsa, A. and Wahlster, W. (Eds.),User Models in Dialog Systems. Springer-Verlag, Berlin, pp. 74–107.

    Google Scholar 

  • Chin, D. N. (1992). Intelligent Inferfaces as Agents. In Sullivan, J. and Tyler, S. (Eds.),Intelligent User Interfaces, ACM Press, New York, pp. 177–206.

    Google Scholar 

  • Clancey, W. J. (1986). From GUIDON to NEOMYCIN and HERACLES in Twenty Short Lessons: ONR Final Report 1979–1985.AI Magazine 7(3), 40–60.

    Google Scholar 

  • Cohen, R., Song, F., Spencer, B. and van Beek, P. (1991). Exploiting Temporal and Novel Information from the User in Plan Recognition.User Modeling and User-Adapted Interaction 1(2), 125–148.

    Google Scholar 

  • DeKleer, J. (1986). An Assumption-Based TMS.Artificial Intelligence 28, 127–162.

    Google Scholar 

  • Dols, F. J. H. and van der Sloot, K. (1992). Modelling Mutual Effects in Belief-based Interactive Systems. In André, E., Cohen, R., Graf, W., Kass, B., Paris, C. and Wahlster, W. (Eds.),Proceedings of UM92, Third International Workshop on User Modeling, pp. 3–21. Available as DFKI Document D-92-17, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Stulsatzenhasweg 3, D-6600 Saarbrücken 11, FRG.

    Google Scholar 

  • Doyle, J. (1979). A Truth Maintenance System.Artificial Intelligence 12, 231–272.

    Google Scholar 

  • Eller, R. and Carberry, S. (1991). A Meta-Rule Approach to Flexible Plan Recognition in Dialogue.User Modeling and User-Adapted Interaction 2(1–2), 27–53.

    Google Scholar 

  • Finin, T. W. (1989). GUMS — A General User Modeling Shell. In Kobsa, A. and Wahlster, W. (Eds.),User Models in Dialog Systems. Springer-Verlag, Berlin, pp. 411–430.

    Google Scholar 

  • Goldman, R. and Charniak, E. (1988). A Probabilistic ATMS for Plan Recognition. In theAAAI-88 Workshop on Plan Recognition, St. Paul, August.

  • Goldstein, I. P. (1982). The Genetic Graph: A Representation for the Evolution of Procedural Knowledge. In Sleeman, D. H. and Brown, J. S. (Eds.),Intelligent Tutoring Systems. Academic Press, New York, pp. 51–77.

    Google Scholar 

  • Huang, X, McCalla, G. I., Greer, J. E. and Neufeld, E. (1991). Revising Deductive Knowledge and Stereotypical Knowledge in a Student Model.User Modeling and User-Adapted Interaction 1(1), 87–115.

    Google Scholar 

  • Jameson, A. (1992). Generalizing the Double-Stereotype Approach: a Psychological Perspective. In André, E., Cohen, R., Graf, W., Kass, B., Paris, C. and Wahlster, W. (Eds.),Proceedings of UM92, Third International Workshop on User Modeling, pp. 69–83. Available as DFKI Document D-92-17, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Stulsatzenhasweg 3, D-6600 Saarbrücken 11, FRG.

    Google Scholar 

  • Jennings, Higuchi, Liu (1991). A Personal News Service Using a Neural Network User Model. InThe Proceedings of the IJCAI-91 Workshop on Agent Modelling for Intelligent Interaction, pp. 1–33.

  • Kay, J. (1989). A Toolkit for User Modeling. In theProceedings of the Second International Workshop on User Modeling, Honolulu, HI.

  • Katz, S. and Lesgold, A. (1992). Approaches to Student Modeling in the Sherlock Tutors. In André, E., Cohen, R., Graf, W., Kass, B., Paris, C. and Wahlster, W. (Eds.),Proceedings of UM92, Third International Workshop on User Modeling, pp. 205–230. Available as DFKI Document D-92-17, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Stulsatzenhasweg 3, D-6600 Saarbrücken 11, FRG.

    Google Scholar 

  • Kass, R. (1991). Building a User Model Implicitly from a Cooperative Advisory Dialog.User Modeling and User-Adapted Interaction 1(3), 203–258.

    Google Scholar 

  • Kautz, H. A. (1990). A Circumscriptive Theory of Plan Recognition. In Cohen, P., Morgan, J. and Pollack, M. (Eds.),Intentions in Communication. MIT Press, Cambridge, MA, pp. 105–133.

    Google Scholar 

  • Kobsa, A. (1985). VIE-DPM: A User Model in a Natural-Langauge Dialogue System. In Laubsch, J. (Ed.),GWAI-84, 8th German Workshop on Artificial Intelligence, Springer, Berlin.

    Google Scholar 

  • Kobsa, A. (1992). Towards Inferences in BGP-MS: Combining Modal Logic and Partition Hierarchies for User Modeling (Preliminary Report). In André, E., Cohen, R., Graf, W., Kass, B., Paris, C. and Wahlster, W. (Eds.),Proceedings of UM92, Third International Workshop on User Modeling, pp. 35–41. Available as DFKI Document D-92-17, Deutsches Forschungszentrum für Künstliche Intelligenz GmbH, Stulsatzenhasweg 3, D-6600 Saarbrücken 11, FRG.

    Google Scholar 

  • Litman, D. and Allen, J. F. (1987). A Plan Recognition Model for Subdialogues in Conversation.Cognitive Science 11, 163–200.

    Google Scholar 

  • Macmillan, S. A. (1983).User Models to Personalize an Intelligent Agent. Doctoral dissertation, School of Education, Stanford University.

  • Mayfield, J. (1992). Controlling Inference in Plan Recognition.User Modeling and User-Adapted Interaction 2(1), 55–82.

    Google Scholar 

  • Miller, M. L. (1982). A Structural Planning Environment. In Sleeman, D. H. and Brown, J. S. (Eds.),Intelligent Tutoring Systems. Academic Press, New York, pp. 119–135.

    Google Scholar 

  • Morik, K. (1989). User Models and Conversational Settings: Modeling the User's Wants. In Kobsa, A. and Wahlster, W. (Eds.),User Models in Dialog Systems. Springer, Berlin, pp. 364–385.

    Google Scholar 

  • Perrault, R. (1990). An Application of Default Logic to Speech Act Theory. In Cohen, P. R., Morgan, J. and Pollock, M. E. (Eds.),Intentions in Communication. MIT Press, Cambridge, MA.

    Google Scholar 

  • Quilici, A. (1989). Detecting and Responding to Plan-Oriented Misconceptions. In Kobsa, A. and Wahlster, W. (Eds.),User Models in Dialog Systems, Spring-Verlag, Berlin, pp. 108–132.

    Google Scholar 

  • Raskutti, B. and Zukerman, I. (1991). Generation and Selection of Likely Interpretation during Plan Recognition in Task-Oriented Consultation Systems.User Modeling and User-Adapted Interaction 1(4), 323–353.

    Google Scholar 

  • Reiter, R. (1980). A Logic for Default Reasoning.Artificial Intelligence 13, 81–132.

    Google Scholar 

  • Retz-Schmidt, G. (1991). Recognizing Intentions, Interactions, and Causes of Plan Failures.User Modeling and User-Adapted Interaction 1(2), 173–202.

    Google Scholar 

  • Rich, E. (1979). User Modeling via Stereotypes.Cognitive Science 3, 329–354.

    Google Scholar 

  • Searle, J. R. (1969).Speech Acts; An Essay in the Philosophy of Langauge. Cambridge University Press, Cambridge, England.

    Google Scholar 

  • Shafer, G. (1976).A Mathematical Theory of Evidence. Princeton Univ. Press, Princeton, NJ.

    Google Scholar 

  • Wahlster W., Marburger, H., Jameson, A. and Busemann, S. (1983). Over-Answering Yes-No-Questions: Extended Responses in a NL Interface to a Vision System. InProceedings of the Eighth International Joint Conference on Artifical Intelligence, pp. 643–646. Karlsruhe, West Germany, August.

  • Wilensky, R., Chin, D. N., Luria, M., Martin, J., Mayfield, J. and Wu, D. (1988). The Berkeley UNIX Consultant Project.Computational Linguistics 14(4), December 1988, 35–84.

    Google Scholar 

  • Wu, D., (1991). Active Acquisition of User Models: Implications for Decision-Theoretic Dialog Planning and Plan Recognition.User Modeling and User-Adapted Interaction 1(2), 149–172.

    Google Scholar 

  • Zadeh, L. A. (1965). Fuzzy Sets.Information and Control 8, 338–353.

    Google Scholar 

Download references

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  1. Department of Information and Computer Sciences, University of Hawaii at Manoa, 2565 The Mall, 96822, Honolulu, HI, USA

    David N. Chin

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Chin, D.N. Acquiring user models. Artif Intell Rev 7, 185–197 (1993). https://doi.org/10.1007/BF00849554

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