Consulting a user model to address a user's inferences during content planning

Zukerman, Ingrid; McConachy, Richard

doi:10.1007/bf01099728

Cited by 8 publications

(4 citation statements)

References 19 publications

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“…During discourse planning, their system activated inferences to determine the level and type of cognitive load imposed by a candidate explanation, and adjusted the explanation when this level was deemed excessive. These inferences are similar to those described by Zukerman and McConachy (1993), in the sense that they are applicable to a concept hierarchy and their effect is moderated by factors that re£ect a student's capabilities. However, unlike Zukerman and McConachy's system, Kashihara et al's system learned the values of these factors from interactions with each student.…”

Section: Considering Inferential Patterns^enhancing User Modelssupporting

confidence: 71%

“…Joshi et al, 1984;Lascarides and Oberlander, 1992;Mehl, 1994). However, the research described in (Zukerman and McConachy, 1993, 1995Kashihara et al, 1995;Kashihara et al, 1996;Zukerman et al,1996;Horacek, 1997) is of particular interest, since these researchers distinguish between the inferences drawn by different types of users. McConachy (1993, 2001), Zukerman et al (1996) and Horacek (1997) use inference rules to model a user's inferences in systems that generate explanations.…”

Section: Considering Inferential Patterns^enhancing User Modelsmentioning

confidence: 99%

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Zukerman

Litman

2001

User Modeling and User-Adapted Interaction

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Abstract. The ¢elds of user modeling and natural language processing have been closely linked since the early days of user modeling. Natural language systems consult user models in order to improve their understanding of users' requirements and to generate appropriate and relevant responses. At the same time, the information natural language systems obtain from their users is expected to increase the accuracy of their user models. In this paper, we review natural language systems for generation, understanding and dialogue, focusing on the requirements and limitations these systems and user models place on each other.We then propose avenues for future research.

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Section: Considering Inferential Patterns^enhancing User Modelssupporting

confidence: 71%

Section: Considering Inferential Patterns^enhancing User Modelsmentioning

confidence: 99%

Untitled

Zukerman

Litman

2001

User Modeling and User-Adapted Interaction

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“…Most part of the early works on adaptive hypermedia was centered around adaptive text presentation (Beaumont, 1994;Böcker et al, 1990;Boyle & Encarnacion, 1994;Brusilovsky, 1992b;de Rosis et al, 1993;Fischer et al, 1990). This direction of research was influenced by the research on adaptive explanation and adaptive presentation in intelligent systems (Moore & Swartout, 1989;Paris, 1988;Zukerman & McConachy, 1993). As we will show in the following sections, there are a number of different techniques for adaptive text presentation.…”

Section: Adaptive Presentationmentioning

confidence: 99%

Methods and Techniques of Adaptive Hypermedia

Brusilovsky¹

1998

Adaptive Hypertext and Hypermedia

430

568

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Adaptive hypermedia is a new direction of research within the area of adaptive and user model-based interfaces. Adaptive hypermedia (AH) systems build a model of the individual user and apply it for adaptation to that user, for example, to adapt the content of a hypermedia page to the user's knowledge and goals, or to suggest the most relevant links to follow. AH systems are used now in several application areas where the hyperspace is reasonably large and where a hypermedia application is expected to be used by individuals with different goals, knowledge and backgrounds. This paper is a review of existing work on adaptive hypermedia. The paper is centered around a set of identified methods and techniques of AH. It introduces several dimensions of classification of AH systems, methods and techniques and describes the most important of them.

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“…Hence a model of the user's beliefs is essential in order to generate discourse that takes into consideration his or her possible inferences. 6 In this section we present a brief description of the user model used by WISHFUL, which represents a user's beliefs and inferences [a detailed description of this model appears in Zukerman and McConachy (1993a)].…”

Section: The User Modelmentioning

confidence: 99%

Wishful: A Discourse Planning System That Considers a User's Inferences

Zukerman

McConachy

2001

Computational Intelligence

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The explicit consideration of an addressee's inferences during discourse planning affects the content and coherence of the generated discourse. The content of the discourse is affected because the consideration of an addressee's inferences may require the addition of information that addresses erroneous inferences or suggest the omission of easily inferred information. The coherence of the discourse is affected because the generated discourse should incorporate inferential relations that emerge from the consideration of an addressee's inferences. In this article, we describe a discourse planner that takes into consideration a user's inferences. In particular, we discuss its content planning and discourse structuring mechanisms. The content planning mechanism generates a set of rhetorical devices that achieves a given communicative goal. The discourse structuring mechanism takes into consideration schematic, inferential, and prescriptive relations between these rhetorical devices in order to organize them into a coherent sequence. Our discourse planner has been implemented in a system called WISHFUL that generates explanations about concepts in technical domains. We evaluated WISHFUL's performance to test the effect of considering a user's inferences during content planning and discourse organization and also to determine the suitability of the discourse produced by WISHFUL for different types of users. The results of our evaluation endorse the ideas embodied in the WISHFUL system.

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Consulting a user model to address a user's inferences during content planning

Cited by 8 publications

References 19 publications

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Methods and Techniques of Adaptive Hypermedia

Wishful: A Discourse Planning System That Considers a User's Inferences

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