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Clustering top-ranking sentences for information access

Tombros, A. and Jose, J. and Ruthven, I. (2004) Clustering top-ranking sentences for information access. In: Research and AdvancedTechnology for Digital Libraries. Lecture Notes in Computer Science . Lecture Notes in Computer Science, Springer, Berlin, pp. 523-528. ISBN 3-540-40726-3

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Abstract

In this paper we propose the clustering of top-ranking sentences (TRS) for effective information access. Top-ranking sentences are selected by a query-biased sentence extraction model. By clustering such sentences, we aim to generate and present to users a personalised information space. We outline our approach in detail and we describe how we plan to utilise user interaction with this space for effective information access. We present an initial evaluation of TRS clustering by comparing its effectiveness at providing access to useful information to that of document clustering.

Item type: Book Section
ID code: 2459
Keywords: top-ranking sentences, TRS, information access, extraction model, Electronic computers. Computer science
Subjects: Science > Mathematics > Electronic computers. Computer science
Department: Faculty of Science > Computer and Information Sciences
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Depositing user: Strathprints Administrator
Date Deposited: 17 Jan 2007
Last modified: 06 Sep 2014 03:47
URI: http://strathprints.strath.ac.uk/id/eprint/2459

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