Challenges Of Discourse Processing
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Discourse Analysis
'Discourse Analysis: Investigating Processes of Social Construction' reflects on the practice of analyzing discourse and the potential for revealing the processes of social construction that constitute social and organizational life.
Discourse Processing
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
Challenges of Discourse Processing
Author: Patrick Saint-Dizier
language: en
Publisher: Cambridge Scholars Publishing
Release Date: 2014-03-17
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.