User models have recently attracted much research interest in the field of artificial intelligence dialog systems. It has become evident that a flexible user-oriented dialog behavior of such systems can be realized only if the system disposes of a model of the user, containing assumptions about the users background knowledge as well as the users 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 interaction with the user. This volume is the first survey pertaining to the field of user modeling. Most of the prominent international researchers in this area have contributed to this volume. Their papers are grouped into four sections: The introductory section contains a general view of the field as a whole, and a number of surveys of specific problems and techniques in user modeling. Sections two and three describe eight user modeling systems, with the focus lying on the automatic creation and exploitation of assumptions about the user respectively. The final section discusses several limits of current systems, and proposes solutions as to how some of the shortcomings might be overcome. In order to increase the quality and the coherency of the volume, each paper has been reviewed by all other contributors. Cross-references have been integrated wherever appropriate. All contributions are introduced in editorial prefaces pertaining to each section. A subject index and an extensive bibliography supplement the book.

Computational Models of Mixed-Initiative Interaction brings together research that spans several disciplines related to artificial intelligence, including natural language processing, information retrieval, machine learning, planning, and computer-aided instruction, to account for the role that mixed initiative plays in the design of intelligent systems. The ten contributions address the single issue of how control of an interaction should be managed when abilities needed to solve a problem are distributed among collaborating agents. Managing control of an interaction among humans and computers to gather and assemble knowledge and expertise is a major challenge that must be met to develop machines that effectively collaborate with humans. This is the first collection to specifically address this issue.

Hypertext/hypermedia systems and user-model-based adaptive systems in the areas of learning and information retrieval have for a long time been considered as two mutually exclusive approaches to information access. Adaptive systems tailor information to the user and may guide the user in the information space to present the most relevant material, taking into account a model of the user's goals, interests and preferences. Hypermedia systems, on the other hand, are `user neutral': they provide the user with the tools and the freedom to explore an information space by browsing through a complex network of information nodes. Adaptive hypertext and hypermedia systems attempt to bridge the gap between these two approaches. Adaptation of hypermedia systems to each individual user is increasingly needed. With the growing size, complexity and heterogeneity of current hypermedia systems, such as the World Wide Web, it becomes virtually impossible to impose guidelines on authors concerning the overall organization of hypermedia information. The networks therefore become so complex and unstructured that the existing navigational tools are no longer powerful enough to provide orientation on where to search for the needed information. It is also not possible to identify appropriate pre-defined paths or subnets for users with certain goals and knowledge backgrounds since the user community of hypermedia systems is usually quite inhomogeneous. This is particularly true for Web-based applications which are expected to be used by a much greater variety of users than any earlier standalone application. A possible remedy for the negative effects of the traditional `one-size-fits-all' approach in the development of hypermedia systems is to equip them with the ability to adapt to the needs of their individual users. A possible way of achieving adaptivity is by modeling the users and tailoring the system's interactions to their goals, tasks and interests. In this sense, the notion of adaptive hypertext/hypermedia comes naturally to denote a hypertext or hypermedia system which reflects some features of the user and/or characteristics of his system usage in a user model, and utilizes this model in order to adapt various behavioral aspects of the system to the user. This book is the first comprehensive publication on adaptive hypertext and hypermedia. It is oriented towards researchers and practitioners in the fields of hypertext and hypermedia, information systems, and personalized systems. It is also an important resource for the numerous developers of Web-based applications. The design decisions, adaptation methods, and experience presented in this book are a unique source of ideas and techniques for developing more usable and more intelligent Web-based systems suitable for a great variety of users. The practitioners will find it important that many of the adaptation techniques presented in this book have proved to be efficient and are ready to be used in various applications.

TV viewers today are exposed to overwhelming amounts of information, and challenged by the plethora of interactive functionality provided by current set-top boxes. To ensure broad adoption of this technology by consumers, future Digital Television will have to take usability issues thoroughly into account. In particular, serious attention must be paid to facilitate the selection of content on an individual basis, and to provide easy-to-use interfaces that satisfy viewers' interaction requirements.

This volume collects selected research reports on the development of personalized services for Interactive TV. Drawing upon contributions from academia and industry in the US, Europe and Asia, this book represents a comprehensive picture of leading edge research in personalized television.

This state-of-the-art survey provides a systematic overview of the ideas and techniques of the adaptive Web and serves as a central source of information for researchers, practitioners, and students. The volume constitutes a comprehensive and carefully planned collection of chapters that map out the most important areas of the adaptive Web, each solicited from the experts and leaders in the field.

TV viewers today are exposed to overwhelming amounts of information, and challenged by the plethora of interactive functionality provided by current set-top boxes. To ensure broad adoption of this technology by consumers, future Digital Television will have to take usability issues thoroughly into account. In particular, serious attention must be paid to facilitate the selection of content on an individual basis, and to provide easy-to-use interfaces that satisfy viewers' interaction requirements.

This volume collects selected research reports on the development of personalized services for Interactive TV. Drawing upon contributions from academia and industry in the US, Europe and Asia, this book represents a comprehensive picture of leading edge research in personalized television.

Computational Models of Mixed-Initiative Interaction brings together research that spans several disciplines related to artificial intelligence, including natural language processing, information retrieval, machine learning, planning, and computer-aided instruction, to account for the role that mixed initiative plays in the design of intelligent systems. The ten contributions address the single issue of how control of an interaction should be managed when abilities needed to solve a problem are distributed among collaborating agents. Managing control of an interaction among humans and computers to gather and assemble knowledge and expertise is a major challenge that must be met to develop machines that effectively collaborate with humans. This is the first collection to specifically address this issue.

Hypertext/hypermedia systems and user-model-based adaptive systems in the areas of learning and information retrieval have for a long time been considered as two mutually exclusive approaches to information access. Adaptive systems tailor information to the user and may guide the user in the information space to present the most relevant material, taking into account a model of the user's goals, interests and preferences. Hypermedia systems, on the other hand, are `user neutral': they provide the user with the tools and the freedom to explore an information space by browsing through a complex network of information nodes. Adaptive hypertext and hypermedia systems attempt to bridge the gap between these two approaches. Adaptation of hypermedia systems to each individual user is increasingly needed. With the growing size, complexity and heterogeneity of current hypermedia systems, such as the World Wide Web, it becomes virtually impossible to impose guidelines on authors concerning the overall organization of hypermedia information. The networks therefore become so complex and unstructured that the existing navigational tools are no longer powerful enough to provide orientation on where to search for the needed information. It is also not possible to identify appropriate pre-defined paths or subnets for users with certain goals and knowledge backgrounds since the user community of hypermedia systems is usually quite inhomogeneous. This is particularly true for Web-based applications which are expected to be used by a much greater variety of users than any earlier standalone application. A possible remedy for the negative effects of the traditional `one-size-fits-all' approach in the development of hypermedia systems is to equip them with the ability to adapt to the needs of their individual users. A possible way of achieving adaptivity is by modeling the users and tailoring the system's interactions to their goals, tasks and interests. In this sense, the notion of adaptive hypertext/hypermedia comes naturally to denote a hypertext or hypermedia system which reflects some features of the user and/or characteristics of his system usage in a user model, and utilizes this model in order to adapt various behavioral aspects of the system to the user. This book is the first comprehensive publication on adaptive hypertext and hypermedia. It is oriented towards researchers and practitioners in the fields of hypertext and hypermedia, information systems, and personalized systems. It is also an important resource for the numerous developers of Web-based applications. The design decisions, adaptation methods, and experience presented in this book are a unique source of ideas and techniques for developing more usable and more intelligent Web-based systems suitable for a great variety of users. The practitioners will find it important that many of the adaptation techniques presented in this book have proved to be efficient and are ready to be used in various applications.

Die Beitrage dieses Tagungsbands befassen sich aus der Sicht der Linguistischen Datenverarbeitung und ihrer benachbarten Disziplinen mit den Interaktionsmoglichkeiten zwischen Mensch und Computer. Zu diesen Disziplinen gehoren z. B. Informatik, insbesondere Software-Engineering und Kunstliche Intelligenz, sowie Psychologie und Arbeitswissenschaft. Sowohl unter praktischen als auch unter theoretischen Gesichtspunkten wird untersucht, wie menschliche Informationsverarbeitung erklart und die Wechselwirkung zwischen Mensch und Computer optimiert werden kann und wie sich geeignete Software entwerfen lasst. Hierbei wird immer wieder die Moglichkeit naturlichsprachlicher Mensch-Computer-Dialoge im Vergleich zu anderen Interaktionsstilen diskutiert. Die Ansatze in den verschiedenen Disziplinen konnen zusammengenommen wichtige Anregungen fur die Linguistische Datenverarbeitung geben.

Die vorliegende Arbeit entstand im Rahmen des yom Osterreichischen Bundesministerium fUr Wissenschaft und Forschung geforderten Projekts 'Die Entwicklung eines Benutzer- modells in Dialogsystemen' des Osterreichischen Forschungsinstituts fUr Artificial Intelligence. Eine erweiterte Fassung der Arbeit wurde von der Technischen Universi- tat Wien als Dissertation zur Erlangung des Doktorats der Technischen Wissenschaften angenommen. Die Drucklegung wurde durch einen Forderungspreis des Theodor-Korner- Stiftungsfonds unterstUtzt. Die Osterreichische Computer Gesellschaft sprach dieser Arbeit den Heinz-Zemanek-Preis 1985 zu. Die Arbeit basiert wesentlich auf den Vorarbeiten meiner Kollegen E. Buchberger, H. Horacek, I. Steinacker und H. Trost. Ohne ihre Beitrage zum natUrlichsprachigen System VIE-LANG ware die Entwicklung der hier vorgestellten Benutzermodellierungs- komponente gar nicht moglich gewesen. Prof. R. Trappl hat als Projektleiter und Erst- begutachter der Dissertation den Fortschritt dieser Arbeit sehr gefordert. Prof. A. M. Tjoa und Prof. E. Neuhold gaben mir wichtige Literaturhinweise auf dem Gebiet der Verteilten Datenbanken, H. Hogrefe, J. Perner und H. Wimmer solche auf dem Gebiet der Kognitiven Psychologie. Herr R. Born und Frau D. Schmauks unterstUtzten mich in Fragen von Sprachstufung, Ontologie und Intension, Herr O. Neumaier bei den ethischen Implikationen dieser Arbeit. Hrn. W. Horn und Hrn. E. Buchberger danke ich fUr die prompte Behebung unzahliger mit meiner Computerbenutzung hoch korrelierter mysterioser Systemfehler. Herr W. Huwig unterstUtzte mich bei der editorischen Aufbereitung dieser Arbeit. Herr O. Neumaier stellte fUr die Anfertigung der Zeichnungen seine wunder schone Schreibmaschine zur VerfUgung, Frl. Sabine Schmauks ihren nicht minder schonen Kinderl en zum Transport derselben.