McCreadie, R. , Santos, R. L.T., Macdonald, C. and Ounis, I. (2018) Explicit diversification of event aspects for temporal summarization. ACM Transactions on Information Systems, 36(3), 25. (doi: 10.1145/3158671)
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150135.pdf - Accepted Version 1MB |
Abstract
During major events, such as emergencies and disasters, a large volume of information is reported on newswire and social media platforms. Temporal summarization (TS) approaches are used to automatically produce concise overviews of such events by extracting text snippets from related articles over time. Current TS approaches rely on a combination of event relevance and textual novelty for snippet selection. However, for events that span multiple days, textual novelty is often a poor criterion for selecting snippets, since many snippets are textually unique but are semantically redundant or non-informative. In this article, we propose a framework for the diversification of snippets using explicit event aspects, building on recent works in search result diversification. In particular, we first propose two techniques to identify explicit aspects that a user might want to see covered in a summary for different types of event. We then extend a state-of-the-art explicit diversification framework to maximize the coverage of these aspects when selecting summary snippets for unseen events. Through experimentation over the TREC TS 2013, 2014, and 2015 datasets, we show that explicit diversification for temporal summarization significantly outperforms classical novelty-based diversification, as the use of explicit event aspects reduces the amount of redundant and off-topic snippets returned, while also increasing summary timeliness.
| Item Type: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Mccreadie, Dr Richard and Macdonald, Professor Craig and Ounis, Professor Iadh |
| Authors: | McCreadie, R., Santos, R. L.T., Macdonald, C., and Ounis, I. |
| College/School: | College of Science and Engineering > School of Computing Science |
| Journal Name: | ACM Transactions on Information Systems |
| Publisher: | ACM Press |
| ISSN: | 1046-8188 |
| ISSN (Online): | 1558-2868 |
| Published Online: | 02 February 2018 |
| Copyright Holders: | Copyright © 2017 The Authors |
| First Published: | First published in ACM Transactions on Information Systems 36(3):25 |
| Publisher Policy: | Reproduced in accordance with the copyright policy of the publisher |
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