Kobsa / Wahlster User Models in Dialog Systems

1989
ISBN: 978-3-642-83230-7
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 471 Seiten, eBook

Reihe: Artificial Intelligence

User models have recently attracted much research interest in the field of artificial intelligence dialog systems. It has become evident that flexible user-oriented dialog behavior of such systems can be achieved only if the system has access to a model of the user containing assumptions about his/her background knowledge as well as his/her goals and plans in consulting the system. Research in the field of user models investigates how such assumptions can be automatically created, represented and exploited by the system in the course of an "on-line" interaction with the user. The communication medium in this interaction need not necessarily be a natural language, such as English or German. Formal interaction languages are also permit ted. The emphasis is placed on systems with natural language input and output, however. A dozen major and several more minor user modeling systems have been de signed and implemented in the last decade, mostly in the context of natural-language dialog systems. The goal of UM86, the first international workshop on user model ing, was to bring together the researchers working on these projects so that results could be discussed and analyzed, and hopefully general insights be found, that could prove useful for future research. The meeting took place in Maria Laach, a small village some 40 miles south of Bonn, West Germany. 25 prominent researchers were invited to participate.

Zielgruppe

Research

Autoren/Hrsg.

Kobsa, Alfred

Wahlster, Wolfgang

Weitere Mitwirkende

Carberry, S.

Carbonell, J.G.

Chin, D.N.

Cohen, R.

Fain Lehman, J.

Finin, T.W.

Jameson, A.

Jones, M.

Kass, R.

Kobsa, A.

McCoy, K.F.

Morik, K.

Paris, C.L.

Quilici, A.E.

Rich, E.

Sparck Jones, K.

Wahlster, W.

Inhaltsverzeichnis

I. A Survey of User Modeling.- 1 User Models in Dialog Systems.- 2 Stereotypes and User Modeling.- 3 A Taxonomy of Beliefs and Goals for User Models in Dialog Systems.- II. Building User Models.- 4 KNOME: Modeling What the User Knows in UC.- 5 Detecting and Responding to Plan-Oriented Misconceptions.- 6 Plan Recognition and Its Use in Understanding Dialog.- 7 Learning the User’s Language: A Step Towards Automated Creation of User Models.- III. Exploiting User Models.- 8 The Use of Explicit User Models in a Generation System for Tailoring Answers to the User’s Level of Expertise.- 9 Highlighting a User Model to Respond to Misconceptions.- 10 But What Will the Listener Think? Belief Ascription and Image Maintenance in Dialog.- 11 Incorporating User Models into Expert Systems for Educational Diagnosis.- IV. Shortcomings of Current Models, Prospects for the Future.- 12 Realism About User Modeling.- 13 User Models and Conversational Settings: Modeling the User’s Wants.- 14 Student Modeling in Intelligent Tutoring Systems — Implications for User Modeling.- 15 GUMS — A General User Modeling Shell.- Appendices.- List of Contributors.