Discourse Processing here is framed as marking up a text with structural descriptions on several levels, which can serve to support many language-processing or text-mining tasks. We first explore some ways of assigning structure on the document level: the logical document structure as determined by the layout of the text, its genre-specific content structure, and its breakdown into topical segments. Then the focus moves to phenomena of local coherence. We introduce the problem of coreference and look at methods for building chains of coreferring entities in the text. Next, the notion of coherence relation is introduced as the second important factor of local coherence. We study the role of connectives and other means of signaling such relations in text, and then return to the level of larger textual units, where tree or graph structures can be ascribed by recursively assigning coherence relations. Taken together, these descriptions can inform text summarization, information extraction, discourse-aware sentiment analysis, question answering, and the like. Table of Contents: Introduction / Large Discourse Units and Topics / Coreference Resolution / Small Discourse Units and Coherence Relations / Summary: Text Structure on Multiple Interacting Levels

Research on discourse (or text) processing has only recently come into its own. It builds on the work of text analysis which has a long and distinguished history, but modern developments in psychology (e.g. memory research), artificial intelligence, linguistics and philosophy have contributed to this emergence in the last decade as a lively and promising research area.This book contains 46 selected and edited contributions from the International Symposium held in Fribourg in 1981, and represents a truly international overview of the developments in research on written and oral discourse. The contributions have been grouped according to problem area and not according to methodology, with the intention of focusing on the important issues in the field of discourse processing and of showing how diverse approaches contribute to a better understanding of the problems involved. The main themes are: text structure, coherence, inference, memory processes, attention and control, goal perspectives, and educational implications.

In this interdisciplinary discussion on mental models, researchers from various areas in cognitive science tackle the following questions: What is a mental model? What are the prospects and limitations in applying the mental model notion in cognitive science? How can the ideas on the nature of mental models and their mode of operation be empirically substantiated? The primary goal of the research group was to work out a definition of mental models that embraces the overall use of this construct in cognitive science as well as the more specific conceptions used in particular research domains such as cognitive linguistics. Theoretical claims about the properties of mental models were discussed and their tenability evaluated against the empirical evidence.The volume is divided into three parts. Fundamental aspects of mental models are presented in the first section, the following part contains contributions to the function of mental models in discourse processing, and finally problems of mental models in reasoning and problem solving are outlined.

This Handbook is a comprehensive overview of the multidisciplinary field of discourse processes. The editors hope to foster a more interdisciplinary approach to discourse processing with this Handbook, while simultaneously developing an appreciation within the field for multiple methods of establishing rigorous scientific claims. The field of discourse processes is currently fueled by seven dominant approaches: * discourse psychology; * corpus analysis; * computational discourse; * discourse technologies; * conversation analysis; * hybrid qualitative and quantitative approaches; and * cultural foundations. The contributors also discuss future trends in research, including corpus analyses, the integration of neuroscience with discourse research, and the development of more advanced computer technologies for analyzing discourse.

Discourse analysis remains an unresolved challenge in Computational Linguistics, in spite of the numerous theoretical works that have been developed in the past two decades. This situation is mainly due to the complexity of discourse constructions whose recognition often involves language analysis associated with domain knowledge and reasoning. Technical documents, such as procedures, requirements, and product manuals, must be relatively constrained in terms of language diversity and complexity: the goal is to make sure that users can efficiently and accurately understand these documents. For that purpose, these documents often follow authoring guidelines. These constraints make it possible to develop an accurate discourse analysis of technical documents which can be used to model their contents and to improve their overall quality. This book shows that linguistic analysis and natural language processing methods can efficiently be used to automatically recognize the discourse structures of technical documents, independently of the industrial sector and activity that is considered. Furthermore, the book presents well-founded and concrete solutions, which can be deployed in industrial contexts for various types of applications. This book begins with a presentation of the different types of technical texts. Their structure is then developed in conjunction with a survey of a number of authoring guidelines developed in the industry. The TextCoop platform and the Dislog language, designed for discourse analysis, are then presented with a large number of concrete examples, allowing readers to develop their own applications. The book concludes with an in-depth investigation of the structure of procedures and requirements.