Abstract
This paper presents a computational strategy for reasoning on a multifaceted user model to generate definitions tailored to the user's needs in a task-oriented dialogue. The strategy takes into account the current focus of attention in the user's partially constructed plan, the user's domain knowledge, and the user's receptivity to different kinds of information. It constructs a definition by weighting both the strategic predicates that might comprise a definition and the propositions that might be used to fill them. These weights are used to construct a definition that includes the information deemed most useful, using information of lesser importance as necessary to adhere to common rhetorical practices. This strategy reflects our hypothesis that beliefs about the appropriate content of a definition should guide selection of a rhetorical strategy, instead of the choice of a rhetorical strategy determining content.
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Margaret Sarner is a Senior Consulting Software Specialist at the E.I. duPont Chemical Company. She received her Ph.D. in Computer and Information Sciences from the University of Delaware. Her research interests include user modeling and natural language generation. This paper is based on her dissertation work.
Sandra Carberry is an associate professor of computer science at the University of Delaware. Her research interests include discourse understanding, user modeling, planning and plan recognition, and intelligent natural language interfaces. Much of her research has focused on developing robust models of plan recognition; this work is part of a long-term project to develop strategies for providing intelligent responses.
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Sarner, M.H., Carberry, S. Generating tailored definitions using a multifaceted user model. User Model User-Adap Inter 2, 181–210 (1992). https://doi.org/10.1007/BF01104704
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DOI: https://doi.org/10.1007/BF01104704