Automatic discourse structure detection using shallow textual continuity
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AbstractA shallow natural language processing approach to discourse structure detection based on the analysis of textual continuity is described. What distinguishes it from previous research is that it does not work toward on the discovery of the formal subtopic structures. In contrast, attention is focused in uncovering the main factors in textual continuity and simulating a dynamic detection mechanism of cohesive sentence-based fragments. A connectionist filtering algorithm is used to capture the textual continuity as one of the structural backbone of text. As a result, the content conveyed by text with discontinuous topic sequence is, on average, most unlikely to be included in the resultant discourse structure. A prototype and its evaluation with various statistics are included. (C) 2003 Elsevier Ltd. All rights reserved.
All Author(s) ListChan SWK
Journal nameInternational Journal of Human-Computer Studies
Year2004
Month7
Day1
Volume Number61
Issue Number1
PublisherACADEMIC PRESS LTD ELSEVIER SCIENCE LTD
Pages138 - 164
ISSN1071-5819
LanguagesEnglish-United Kingdom
Web of Science Subject CategoriesComputer Science; Computer Science, Cybernetics; COMPUTER SCIENCE, CYBERNETICS; Engineering; Ergonomics; ERGONOMICS; Psychology; Psychology, Multidisciplinary; PSYCHOLOGY, MULTIDISCIPLINARY

Last updated on 2020-09-07 at 02:42