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Exploring clustering for multi-document Arabic summarisation

El-Haj, M and Kruschwitz, U and Fox, C (2011) Exploring clustering for multi-document Arabic summarisation. In: UNSPECIFIED, ? - ?.

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Abstract

In this paper we explore clustering for multi-document Arabic summarisation. For our evaluation we use an Arabic version of the DUC-2002 dataset that we previously generated using Google Translate. We explore how clustering (at the sentence level) can be applied to multi-document summarisation as well as for redundancy elimination within this process. We use different parameter settings including the cluster size and the selection model applied in the extractive summarisation process. The automatically generated summaries are evaluated using the ROUGE metric, as well as precision and recall. The results we achieve are compared with the top five systems in the DUC-2002 multi-document summarisation task. © 2011 Springer-Verlag Berlin Heidelberg.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Additional Information: Published proceedings: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Subjects: P Language and Literature > P Philology. Linguistics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Users 161 not found.
Date Deposited: 19 Oct 2012 10:02
Last Modified: 23 Jan 2019 01:15
URI: http://repository.essex.ac.uk/id/eprint/3882

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