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In face-to-face conversation humans frequently use deicfic gestures parallel to verbal descriptions for referent identification. Such a multimodal form of communication is of great importance for intelligent interfaces, because it simplifies and speeds up reference to objects in a visual context. Natural pointing behavior is very flexible, but possibly ambiguous or vague, so that without a careful analysis of the discourse context of a gesture there would be a high risk of reference failure. The subject of this paper is how the user and discourse models of an intelligent interface influence the comprehension and, production of natural language with coordinated pointing, and conversely how multimodal communication influences the user model and the discourse model.

this paper is that neither has been implemented." ([Vaughan and McDonald, 1986], page 95). Although Meteer [1990] gives a detail description of the relationship between text structure and revision it is unclear how the proposed model could contribute to the choice problem of paraphrases (see section 5.2). How- ever, from the approach described above and from the system described in [Meteer, 1990] we can draw the following conclusions. Only the generatoFs input is marked. If the generator encounters alternative realizations the revision component is asked to make the decision. However, to be able to do this it needs detailed knowledge about the grammar. Therefore grammatical knowledge has to be duplicated. The linguistic realization component used in [Meteer, 1990] is MUMBLE-86 [McDonald, 1986]. The text structural representation level must completely specify the infor- mation to be expressed by the utterance. The mapping has to ensure that all the necessary linguistic information is present. Mumblers procedural grammar is used only for generation purposes. Therefore it is without reach for the revision model to take into account relevant sources of ambiguities

One characteristic of intelligence is adaptation. Computers should adapt to who is using them, how, why, when and where. The computer's representation of the user is called a user model; user modeling is concerned with developing techniques for representing the user and acting upon this information. The Doppelg anger system consists of a set of techniques for gathering, maintaining, and acting upon information about individuals, and illustrates my approach to user modeling. Work on Doppelg anger has been heavily influenced by the field of machine learning. This thesis has a twofold purpose: first, to set forth guidelines for the integration of machine learning techniques into user modeling, and second, to identify particular user modeling tasks for which machine learning is useful.

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In this paper we discuss a proposed user knowledge modeling architecture for the ICICLE system, a language tutoring application for deaf learners of written English. The model will represent the language proficiency of the user and is designed to be referenced during both writing analysis and feedback production. We motivate our model design by citing relevant research on second language and cognitive skill acquisition, and briefly discuss preliminary empirical evidence supporting the design. We conclude by showing how our design can provide a rich and robust information base to a language assessment / correction application by modeling user proficiency at a high level of granularity and specificity.

This proposal paper is being presented in partial fulfillment of the Ph.D. requirements of the Department of Computer and Information Sciences at the University of Delaware. In this paper, I discuss a user modeling architecture for ICICLE, a natural language system intended for use as a writing tutor for deaf learners of written English. This proposed design, intended to model dynamic aspects of a learner over the passage of time, the acquisition of new knowledge, and multiple sessions with the system, includes components to track the history of interaction with a given user as well as a very complex, dynamic model of user interlanguage grammar and domain knowledge. It has been based on research in language acquisition and in the acquisition of cognitive skills. The focus of the work described in this proposal is the development of the model of interlanguage status, which will be used in the analysis of user language production and in the generation of user-tailored explanations. Conte...

In this paper the definitions of and approaches to user modeling in natural language dialog systems have been reviewed. The contents of user models are discussed; how user modeling in different research areas relates to user modeling are reviewed; examples of some techniques for building user models through natural language interaction and observed behavior in other media channels are given. Furthermore, the uses of user models in natural language dialog systems are discussed, as well as the implications of employing user models. It is concluded that natural language aspects of user modeling is needed to complement traditional user modeling in high-functionality applications.

The field of adaptive hypermedia is a little over a decade old. It has a rich history in a range of fields such as artificial intelligence, user modelling, intelligent tutoring systems and hypertext. Early adaptive hypermedia work concentrated on applicationled research; developing a range of systems for specific purposes. In 1996, Peter Brusilovsky reviewed the state-of-the-art and proposed a taxonomy of adaptive hypermedia techniques, thereby providing the means to categorise adaptive hypermedia systems. Since then, several practical frameworks for adaptive hypermedia applications have been produced, in addition to formal models for formalising adaptive hypermedia applications. This thesis presents a new framework for adaptive hypermedia systems based on agent technology, a field of research largely ignored within the adaptive community. Conceptually, this framework occupies a middle ground between the formal reference models for adaptive hypermedia and application-specific frameworks. This framework provides the means to implement formal models using variety of architectural approaches.

Abstract: Natural language processing is a prerequisite for advanced knowledge-based systems since the ability to acquire, retrieve, exploit and present knowledge critically depends on natural language comprehension and production. Natural language concepts guide the interpretation of what we see, hear, read, or experience with other senses. In the first part of the paper, we illustrate the needed capabilities of cooperative dialog systems with a detailed example: the interaction between a customer and a clerk at an information desk in a train station. It is shown, that natural language systems cannot just rely on knowledge about syntactical and semantical aspects of language but also have to exploit conceptual and inferential knowledge, and a user model. In the remainder, we analyze and evaluate three natural language systems which were introduced to the commercial market in 1985: Language Craft ™ by