User Models in Dialog Systems

Wahlster, Wolfgang; Kobsa, Alfred

doi:10.1007/978-3-642-83230-7_1

Cited by 93 publications

(41 citation statements)

References 37 publications

(36 reference statements)

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“…These channels capture 226 the idea of shared knowledge about problem domains, communication processes, 227 and agents involved with communicating parties. This notion is very close to the 228 goals of user modeling (Wahlster and Kobsa, 1989). Several researchers worked on 229 the incorporation of user modeling in order to improve the collaborative nature 230 of human-computer systems (for examples see Fischer, 2001).…”

Section: Non-graphical User Interfaces 153mentioning

confidence: 99%

“…Bayesian networks to formal knowledge models as known in symbolic artificial 274 intelligence (Wahlster and Kobsa, 1989 In the area of user interaction this provides us with a clear formalism to connect 294 knowledge about the user, environment, and user aims. 295 An obstacle in connecting and sharing data, is that often the knowledge cap-296 tured within an application is at too low a level of abstraction; it is too domain 297 specific.…”

Section: Semantic Technologies 271mentioning

confidence: 99%

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Ontology-Based User Modeling in an Augmented Audio Reality System for Museums

Hatala

Wakkary

2005

User Model User-Adap Inter

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Abstract. Ubiquitous computing is a challenging area that allows us to further our under-7 standing and techniques of context-aware and adaptive systems. Among the challenges is 8 the general problem of capturing the larger context in interaction from the perspective 9 of user modeling and human-computer interaction (HCI). The imperative to address this 10 issue is great considering the emergence of ubiquitous and mobile computing environments. 11This paper provides an account of our addressing the specific problem of supporting func-12 tionality as well as the experience design issues related to museum visits through user mod-13 eling in combination with an audio augmented reality and tangible user interface system. 14 This paper details our deployment and evaluation of ec (h) Introduction 25Fundamental to human-computer interaction (HCI) is the design of interactive 26 systems that support people's goals and respond to individual backgrounds. In 27 ubiquitous computing it is equally important to consider the influence of context 28 on people's interactions and experiences. The intent is, as Fischer argues "to say 29 the 'right' thing at the 'right' time in the 'right' way" (Fischer, 2001). A critical 30 factor in ubiquitous computing is that what is perceived as "right" is largely med-31 iated by the context within which the users find themselves. 32In the area of user-adapted interaction, user modeling has attempted to address 33 many issues related to HCI. Fischer provides a clear account of the successes and 34 * This paper has not been submitted elsewhere in identical or similar form, nor will it be during the first three months after its submission to UMUAI. is the general problem of capturing the larger context in interaction (see Fischer, 36 2001, pp. 80-81). The imperative to address this issue is great considering the 37 emergence of ubiquitous and mobile computing environments. This paper provides 38 an account of addressing the specific problem of supporting functionality as well 39 as the experience design issues related to museum visits through user modeling in 40 combination with an audio augmented reality and tangible user interface system. 41We developed and tested a museum guide prototype, known as ec(h)o in order 42 to research interaction design, user modeling, and adaptive information retrieval 43 approaches that respond to the richness of a museum visit and the museum con-44 text. 45Our aim is to support the limited input common to tangible user interfaces 46 while maintaining rich and adaptive information output via a three-dimensional 47 audio display. We believe an integrated modeling technique that is weighted toward 48 modeling of implicit communication works well with a tangible user interface in 49 creating a playful and discovery-rich experience. We believe this approach com-50 bined with ontologies and a rule-based system for information retrieval provides 51 a richness of information that is responsive to the context and unique aspects of 52 the museum visitor's interaction. 5...

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Section: Non-graphical User Interfaces 153mentioning

confidence: 99%

Section: Semantic Technologies 271mentioning

confidence: 99%

Ontology-Based User Modeling in an Augmented Audio Reality System for Museums

Hatala

Wakkary

2005

User Model User-Adap Inter

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“…One problem that arises because of the wide variety of users of such tools is to find a way for adapting the presentation to the particular user. Many of the most advanced solutions [20,18,1,9,10] start from the assumption that adaptation should focus on the user's own characteristics, thus, though in different ways, they all try to associate him/her with a reference prototype (also known as the "user model"); the presentation is then adapted to user prototypes. The association between the user and a model is done either a priori, by asking the user to fill a form, or little by little by inducing preferences and interests from the user's choices.…”

Section: Introduction and Related Workmentioning

confidence: 99%

Programming Goal-Driven Web Sites Using an Agent Logic Language

Baldoni

Baroglio

Chiarotto

et al. 2001

Practical Aspects of Declarative Languages

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Abstract. In this paper we show how an agent programming language, based on a formal theory of actions, can be employed to implement adaptive web applications, where a personalized dynamical site generation is guided by the user's needs. For this purpose, we have developed an on-line computer seller in DyLOG, a modal logic programming language which allows one to specify agents acting, interacting, and planning in dynamic environments. Adaptation at the navigation level is realized by dynamically building a presentation plan for solving the problem to assemble a computer, being driven by goals generated by interacting with the user. The planning capabilities of DyLOG are exploited to implement the automated generation of a presentation plan to achieve the goals. The DyLOG agent is the "reasoning" component of a larger system, called WLog, which is described in this paper.

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“…There are a number of efforts to incorporate models of users into knowledge-based systems (Rich, 1983;Clancey, 1986;Kass and Finin, 1987;Fain-Lehman and Carbonell, 1987;Reiser, Anderson and Farrell, 1985;Wahlster and Kobsa, 1988;VanLehn, 1988). In our own User 1 User 2 Figure 11.…”

Section: M3: the Systems' Models Of Usersmentioning

confidence: 99%

The Importance of Models in Making Complex Systems Comprehensible

Fischer

1991

Mental Models and Human-Computer Interaction 2

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Reality is not user-friendly. To cope with, model, and comprehend a complex reality requires complex systems. Complex systems offer power, but they are not without problems. In our research, high functionality computer systems serve as prototypical examples for complex systems and are used to instantiate our framework of cooperative problem solving in joint human-computer systems.Models play a crucial role in the creation and use of these systems and help to increase their comprehensibility. Three different types of models are discussed in this paper: the designers' models of users, the users' models of systems, and the systems' models of users.Innovative system designs supporting human problem-domain communication and providing design environments illustrate the relevance of these models in making complex systems comprehensible.

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User Models in Dialog Systems

Cited by 93 publications

References 37 publications

Ontology-Based User Modeling in an Augmented Audio Reality System for Museums

Ontology-Based User Modeling in an Augmented Audio Reality System for Museums

Programming Goal-Driven Web Sites Using an Agent Logic Language

The Importance of Models in Making Complex Systems Comprehensible

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