Type

Conference Proceedings

Authors

Alan F. Smeaton
Joe Carthy
Nicola Stokes

Subjects

Computer Science

Topics
lexical information retrieval text segmentation news search lexical cohesion digital video chains

Segmenting broadcast news streams using lexical chains (2002)

Abstract In this paper we propose a course-grained NLP approach to text segmentation based on the analysis of lexical cohesion within text. Most work in this area has focused on the discovery of textual units that discuss subtopic structure within documents. In contrast our segmentation task requires the discovery of topical units of text i.e. distinct news stories from broadcast news programmes. Our system SeLeCT first builds a set of lexical chains, in order to model the discourse structure of the text. A boundary detector is then used to search for breaking points in this structure indicated by patterns of cohesive strength and weakness within the text. We evaluate this technique on a test set of concatenated CNN news story transcripts and compare it with an established statistical approach to segmentation called TextTiling.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> Subject = Computer Science
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: Centre for Digital Video Processing (CDVP)
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Information retrieval
Ireland -> Dublin City University -> Subject = Computer Science: Digital video
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres

Full list of authors on original publication

Alan F. Smeaton, Joe Carthy, Nicola Stokes

Experts in our system

1
Alan F. Smeaton
Dublin City University
Total Publications: 450
 
2
Joe Carthy
Dublin City University
Total Publications: 9