Up to now there has been no scientific publication on natural lan guage research that presents a broad and complex description of the current problems of parsing in the context of Artificial Intelli gence. However, there are many interesting results from this domain appearing mainly in numerous articles published in pro fessional journals. In view of this situation, the objective of this book is to enable scientists from different countries to present the results of their research on natural language parsing in the form of more detailed papers than would be possible in professional jour nals. This book thus provides a collection of studies written by well known scientists whose earlier publications have greatly contributed to the development of research on natural language parsing. Jaime G. Carbonell and Philip J. Hayes present in their paper "Robust Parsing Using Multiple Construction-Specific Strategies" two small experimental parsers, implemented to illustrate the advantages of a multi-strategy approach to parsers, with strategies selected according to the type of construction being parsed at any given time. This presentation is followed by the description of a parsing algorithm, integrating some of the best features of the two smaller parsers, including case-frame instantiation and partial pat tern-matching strategies."

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.