Exploring clustering for multi-document Arabic summarisation

El-Haj, Mahmoud and Kruschwitz, Udo and Fox, Chris (2011) Exploring clustering for multi-document Arabic summarisation. In: Information Retrieval Technology. Lecture Notes in Computer Science . Springer, Berlin, pp. 550-561. ISBN 9783642256301

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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.

Item Type: Contribution in Book/Report/Proceedings
Departments: Faculty of Science and Technology > School of Computing & Communications
ID Code: 71271
Deposited By: ep_importer_pure
Deposited On: 17 Oct 2014 11:07
Refereed?: Yes
Published?: Published
Last Modified: 11 Feb 2020 06:09
URI: https://eprints.lancs.ac.uk/id/eprint/71271

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