The University of Southampton
University of Southampton Institutional Repository

Investigating Sentence Weighting Components for Automatic Summarisation

Liang, SF (2006) Investigating Sentence Weighting Components for Automatic Summarisation Liang, S.F., Devlin, S. and Tait, J. (2007). Investigating Sentence Weighting Components for Automatic Summarisation. Information Processing & Management, 43(1), 146-153.

Record type: Article


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.

PDF IP&M_revised-clean.pdf - Other
Download (172kB)

More information

Published date: 2006
Organisations: Electronics & Computer Science


Local EPrints ID: 264982
PURE UUID: 59e3c7d2-e305-4aa5-bdbd-9158aecb95fc

Catalogue record

Date deposited: 18 Dec 2007 14:07
Last modified: 18 Jul 2017 07:30

Export record


Author: SF Liang

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.