Discourse processing
By: Manfred Stede
Series: Synthesis lectures on human language technologies -- # 15
Publisher: Morgan & Claypool
Published: 2012
Place of publication: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA)
Language: eng
Format: [electronic resource] /
Number of pages: 155
ISBN-13: 9781608457359; 9781608457342
Subjects: Discourse analysis; Computational linguistics
Other titles: Synthesis digital library of engineering and computer science.
Description: 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.
Notes: Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (p. 137-154).

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

Also available in print.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.

Title from PDF t.p. (viewed on December 17, 2011).
Table of contents: title: 1. Introduction; title: 2. Large discourse units and topics; title: 2.1 Genre-induced text structure; title: 2.1.1 Logical document structure; title: 2.1.2 Content zones; title: 2.1.3 Example: scientific papers; title: 2.1.4 Example: film reviews; title: 2.2 Topic-based segmentation; title: 2.2.1 Introduction: "What is this all about?"; title: 2.2.2 Exploiting surface cues; title: 2.2.3 Lexical chains; title: 2.2.4 Word distributions; title: 2.2.5 Probabilistic models of segmentation and topics; title: 2.2.6 Combining evidence; title: 2.3 Summary; title: 3. Coreference resolution; title: 3.1 Reference and coreference: an overview; title: 3.2 Corpus annotation; title: 3.3 Entity-based local coherence; title: 3.4 Determining anaphoricity and familiarity status; title: 3.5 Rule-based methods for resolving nominal anaphora; title: 3.5.1 Matching proper names; title: 3.5.2 Pronoun resolution; title: 3.5.3 Resolving definite noun phrases; title: 3.5.4 Web-assisted resolution of 'Other'-anaphora; title: 3.6 Statistical approaches to coreference resolution; title: 3.6.1 Features; title: 3.6.2 Mention-pair models; title: 3.6.3 Alternative models; title: 3.7 Evaluation; title: 3.8 Summary; title: 4. Small discourse units and coherence relations; title: 4.1 Coherence relations; title: 4.2 Segmentation: finding elementary discourse units; title: 4.2.1 Defining EDUs; title: 4.2.2 A subproblem: attribution; title: 4.2.3 Automatic EDU segmentation; title: 4.3 Recognizing coherence relations; title: 4.3.1 Connectives: an introduction; title: 4.3.2 Identifying connectives; title: 4.3.3 Interpreting connectives; title: 4.3.4 Detecting implicit coherence relations; title: 4.3.5 Finding relations: the problem at large; title: 4.4 Coherence-relational text structure; title: 4.4.1 Trees; title: 4.4.2 Parsing coherence-relational trees; title: 4.4.3 Graphs; title: 4.5 Summary: guessing or underspecifying?; title: 5. Summary: text structure on multiple interacting levels; title: A. Sample text; title: Bibliography; title: Author's biography.