User Modelling in Text Generation.

Cover -- Half-title -- Title -- Copyright -- Dedication -- Contents -- List of Figures -- Foreword -- Preface -- 1 Introduction -- 1.1 Natural Language Generation -- 1.1.1 Language variation according to the situation -- 1.2 User modelling in generation -- 1.3 Research method and major results -- 1.4 The domain -- 1.5 System overview -- 1.6 Examples from TAILOR -- 1.7 Limitations -- 1.8 A guide to remaining chapters -- 2 The user model in TAILOR -- 2.1 Contents and use of a user model -- 2.2 Identifying what needs to be in the user model -- 2.3 Determining the level of expertise -- 2.3.1 User type -- 2.3.2 Obtaining information from a dialogue -- 2.3.3 Employing Inference Rules -- 2.3.4 Asking the user questions and using the previous discourse -- 2.4 Conclusions -- 3 The text analysis -- 3.1 Analyzing text -- 3.2 The texts analyzed -- 3.2.1 The textual analysis -- 3.2.2 Analyses of entries from adult encyclopedias and the car manual for experts -- 3.2.3 Texts from junior encyclopedias, high school textbooks, and the car manual for novices -- 3.2.4 Need for directives -- 3.2.5 Summary of the textual analyses -- 3.2.6 Plausibility of this hypothesis -- 3.3 Combining the strategies for users with intermediate levels of expertise -- 3.4 Summary -- 4 The discourse strategies used in TAILOR -- 4.1 Constituency Schema -- 4.2 Process Trace -- 4.3 Requirements of the knowledge base -- 4.4 The process trace: a procedural strategy -- 4.4.1 Identifying the main path and different kinds of links -- 4.4.2 The main path -- 4.4.3 Deciding among several side links or side chains -- 4.5 Strategy representation -- 4.6 Open problems -- 4.7 Summary -- 5 Combining the strategies to describe devices for a wholerange of users -- 5.1 The user model contains explicit parameters -- 5.2 Generating a description based on the user model.

5.2.1 Choosing a strategy for the overall structure of the description -- 5.2.2 Combining the strategies -- 5.3 Examples of texts combining the two strategies -- 5.4 Combining strategies yields a greater variety of texts -- 5.5 Conclusions -- 6 TAILOR system implementation -- 6.1 System overview -- 6.2 The knowledge base and its representation -- 6.2.1 The generalization hierarchies -- 6.2.2 Limitations of the knowledge base -- 6.3 The user model -- 6.4 The textual component -- 6.4.1 Initially selecting a strategy -- 6.4.2 Finding the main path -- 6.4.3 Implementation of the Strategies -- 6.4.4 Stepping through the Constituency Schema -- 6,4.5 The ATN corresponding to the Process Trace -- 6.4.6 Choosing an arc -- 6.5 The Interface -- 6.6 The surface generator -- 6.6.1 The functional grammar and the unification process -- 6.7 Issues pertaining to domain dependency -- 6.8 TAILOR as a question answering system -- 7 Related Work -- 7.1 Related work in user modelling and generation -- 7.1.1 Using stereotypes -- 7.1.2 Modelling and exploiting the user's domain knowledge -- 7.1.3 Using knowledge about the user's plans and goals to generate responses -- 7.1.4 Using reasoning about mutual beliefs to plan an utterance -- 7.1.5 Dealing with misconceptions about the domain -- 7.1.6 Exploiting the speaker's and hearer's 'pragmatic goals' in generation -- 7.2 Related work in psychology and reading comprehension -- 7.3 Summary -- 8 Beyond TAILOR -- 8.1 Main points of this work -- 8.2 Feasibility and extensibility of this approach -- 8.3 Current directions -- 8.3.1 Employing the generator presented here in another domain -- 8.3.2 Building a system with dialogue capabilities -- 8.3.3 Tailoring the phrasing of a text -- 83.4 Bringing the whole generation process under register control -- 8.3.5 Providing a system with adaptive capabilities -- Appendix A -- Appendix B.

Bibliography -- Index.

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Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2024. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.