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Investigating sentence weighting components for automatic summarisation

Investigating sentence weighting components for automatic summarisation
Investigating sentence weighting components for automatic summarisation
The work described here initially formed part of a triangulation exercise to establish the effectiveness of the Query Term Order algorithm. The methodology produced subsequently proved to be a reliable indicator of quality for summarising English web documents. We utilised the human summaries from the Document Understanding Conference data, and generated queries automatically for testing the QTO algorithm. Six sentence weighting schemes that made use of Query Term Frequency and QTO were constructed to produce system summaries, and this paper explains the process of combining and balancing the weighting components. We also examined the five automatically generated query terms in their different permutations to check if the automatic generation of query terms resulting bias. The summaries produced were evaluated by the ROUGE-1 metric, and the results showed that using QTO in a weighting combination resulted in the best performance. We also found that using a combination of more weighting components always produced improved performance compared to any single weighting component.
0306-4573
146-153
Liang, SF
22ac6455-24fb-40d7-b9b6-f8ae62f085fd
Devlin, Siobhan
6df7be0f-0bf2-4e0a-989d-aa9a260beb72
Tait, John
af9fd1be-d213-4bec-88ff-e24f36a2c752
Liang, SF
22ac6455-24fb-40d7-b9b6-f8ae62f085fd
Devlin, Siobhan
6df7be0f-0bf2-4e0a-989d-aa9a260beb72
Tait, John
af9fd1be-d213-4bec-88ff-e24f36a2c752

Liang, SF, Devlin, Siobhan and Tait, John (2006) Investigating sentence weighting components for automatic summarisation. Information Processing & Management, 146-153. (doi:10.1016/j.ipm.2006.05.010).

Record type: Article

Abstract

The work described here initially formed part of a triangulation exercise to establish the effectiveness of the Query Term Order algorithm. The methodology produced subsequently proved to be a reliable indicator of quality for summarising English web documents. We utilised the human summaries from the Document Understanding Conference data, and generated queries automatically for testing the QTO algorithm. Six sentence weighting schemes that made use of Query Term Frequency and QTO were constructed to produce system summaries, and this paper explains the process of combining and balancing the weighting components. We also examined the five automatically generated query terms in their different permutations to check if the automatic generation of query terms resulting bias. The summaries produced were evaluated by the ROUGE-1 metric, and the results showed that using QTO in a weighting combination resulted in the best performance. We also found that using a combination of more weighting components always produced improved performance compared to any single weighting component.

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More information

Published date: 5 July 2006
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 264982
URI: http://eprints.soton.ac.uk/id/eprint/264982
ISSN: 0306-4573
PURE UUID: 59e3c7d2-e305-4aa5-bdbd-9158aecb95fc

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Date deposited: 18 Dec 2007 14:07
Last modified: 14 Mar 2024 07:59

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Contributors

Author: SF Liang
Author: Siobhan Devlin
Author: John Tait

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