dc.contributor.author | BAYOMI, MOSTAFA MOHAMED | |
dc.contributor.author | LEVACHER, KILLIAN | |
dc.contributor.author | LAWLESS, SEAMUS | |
dc.contributor.author | LAVIN, PETER | |
dc.contributor.author | Ghorab, M. Rami | |
dc.contributor.author | O’Connor, Alexander | |
dc.contributor.editor | Métais, F. Meziane, M. Saraee, V. Sugumaran and S. Vadera | en |
dc.date.accessioned | 2016-09-29T12:41:58Z | |
dc.date.available | 2016-09-29T12:41:58Z | |
dc.date.created | June 22-24 | en |
dc.date.issued | 2016 | en |
dc.date.submitted | 2016 | en |
dc.identifier.citation | MOSTAFA MOHAMED BAYOMI, KILLIAN LEVACHER, SEAMUS LAWLESS, PETER LAVIN, M. Rami Ghorab, Alexander O’Connor, 'Towards Evaluating the Impact of Anaphora Resolution on Text Summarisation from a Human Perspective', Springer International Publishing, 2016, Lecture Notes in Computer Science;9612 | en |
dc.identifier.issn | 0302-9743 | |
dc.identifier.other | Y | |
dc.description.abstract | Automatic Text Summarisation (TS) is the process of abstracting key
content from information sources. Previous research attempted to combine
diverse NLP techniques to improve the quality of the produced summaries. The
study reported in this paper seeks to establish whether Anaphora Resolution
(AR) can improve the quality of generated summaries, and to assess whether AR
has the same impact on text from different subject domains. Summarisation
evaluation is critical to the development of automatic summarisation systems.
Previous studies have evaluated their summaries using automatic techniques.
However, automatic techniques lack the ability to evaluate certain factors which
are better quantified by human beings. In this paper the summaries are evaluated
via human judgment, where the following factors are taken into consideration:
informativeness, readability and understandability, conciseness, and the overall
quality of the summary. Overall, the results of this study depict a pattern of
slight but not significant increases in the quality of summaries produced using
AR. At a subject domain level, however, the results demonstrate that the contribution of AR towards TS is domain dependent and for some domains it has a
statistically significant impact on TS. | en |
dc.format.extent | 187 | en |
dc.format.extent | 199 | en |
dc.language.iso | en | en |
dc.publisher | Springer International Publishing | en |
dc.relation.ispartofseries | Lecture Notes in Computer Science;9612 | |
dc.rights | Y | en |
dc.subject | Text summarisation, Anaphora resolution, TextRank | en |
dc.title | Towards Evaluating the Impact of Anaphora Resolution on Text Summarisation from a Human Perspective | en |
dc.title.alternative | International Conference on Applications of Natural Language to Information Systems | en |
dc.type | Conference Paper | en |
dc.type.supercollection | scholarly_publications | en |
dc.type.supercollection | refereed_publications | en |
dc.identifier.peoplefinderurl | http://people.tcd.ie/bayomim | |
dc.identifier.peoplefinderurl | http://people.tcd.ie/selawles | |
dc.identifier.peoplefinderurl | http://people.tcd.ie/lavinpe | |
dc.identifier.peoplefinderurl | http://people.tcd.ie/levachk | |
dc.identifier.rssinternalid | 128477 | |
dc.identifier.doi | 10.1007/978-3-319-41754-7_16 | |
dc.rights.ecaccessrights | openAccess | |
dc.subject.TCDTheme | Intelligent Content & Communications | en |
dc.identifier.rssuri | http://link.springer.com/chapter/10.1007/978-3-319-41754-7_16 | |
dc.subject.darat_thematic | Literature | en |
dc.status.accessible | N | en |
dc.contributor.sponsor | SFI stipend | en |
dc.contributor.sponsorGrantNumber | 12/CE/I2267 | en |
dc.identifier.uri | http://hdl.handle.net/2262/77448 | |