Hostname: page-component-7c8c6479df-995ml Total loading time: 0 Render date: 2024-03-28T08:46:15.735Z Has data issue: false hasContentIssue false

Recovering nonlinearly distributed knowledge: Computing discourse structure in factual reports

Published online by Cambridge University Press:  01 September 1997

ŁUCJA IWAŃSKA
Affiliation:
Department of Computer Science, Wayne State University, Detroit, MI 48202, USA; e-mail: lucja@cs.wayne.edu

Abstract

This paper presents a new type of nonlinear discourse structure found to be very common in free English texts. This structure reflects nonlinear presentation of the information and knowledge conveyed by the texts. It is argued that such nonlinearity is representationally and informationally advantageous because it allows one to create smaller, more compact texts. The paper presents a heuristics-based, relatively domain-independent algorithm for computing this new text structure. The paper discusses good quantitative and qualitative performance of the algorithm, and presents the results of the extensive tests on a large volume of free English texts.

Type
Research Article
Copyright
1997 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)