The Theory and Practice of Discourse Parsing and Summarization

by: Daniel Marcu (Author)

Publisher: Bradford Books

Publication Date: 2000/11/13

Language: English

Print Length: 248 pages

ISBN-10: 0262133725

ISBN-13: 9780262133722

Book Description

This book documents the first serious attempt to construct automatically and use nonsemantic computational structures for text summarization.Until now, most discourse researchers have assumed that full semantic understanding is necessary to derive the discourse structure of texts. This book documents the first serious attempt to construct automatically and use nonsemantic computational structures for text summarization. Daniel Marcu develops a semantics-free theoretical framework that is both general enough to be applicable to naturally occurring texts and concise enough to facilitate an algorithmic approach to discourse analysis. He presents and evaluates two discourse parsing methods:one uses manually written rules that reflect common pattes of usage of cue phrases such as "however" and "in addition to"; the other uses rules that are leaed automatically from a corpus of discourse structures. By means of a psycholinguistic experiment, Marcu demonstrates how a discourse-based summarizer identifies the most important parts of texts at levels of performance that are close to those of humans.Marcu also discusses how the automatic derivation of discourse structures may be used to improve the performance of current natural language generation, machine translation, summarization, question answering, and information retrieval systems.

About the Author

This book documents the first serious attempt to construct automatically and use nonsemantic computational structures for text summarization.Until now, most discourse researchers have assumed that full semantic understanding is necessary to derive the discourse structure of texts. This book documents the first serious attempt to construct automatically and use nonsemantic computational structures for text summarization. Daniel Marcu develops a semantics-free theoretical framework that is both general enough to be applicable to naturally occurring texts and concise enough to facilitate an algorithmic approach to discourse analysis. He presents and evaluates two discourse parsing methods:one uses manually written rules that reflect common pattes of usage of cue phrases such as "however" and "in addition to"; the other uses rules that are leaed automatically from a corpus of discourse structures. By means of a psycholinguistic experiment, Marcu demonstrates how a discourse-based summarizer identifies the most important parts of texts at levels of performance that are close to those of humans.Marcu also discusses how the automatic derivation of discourse structures may be used to improve the performance of current natural language generation, machine translation, summarization, question answering, and information retrieval systems.