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ACL
2015

Joint Graphical Models for Date Selection in Timeline Summarization

7 years 11 months ago
Joint Graphical Models for Date Selection in Timeline Summarization
Automatic timeline summarization (TLS) generates precise, dated overviews over (often prolonged) events, such as wars or economic crises. One subtask of TLS selects the most important dates for an event within a certain time frame. Date selection has up to now been handled via supervised machine learning approaches that estimate the importance of each date separately, using features such as the frequency of date mentions in news corpora. This approach neglects interactions between different dates that occur due to connections between subevents. We therefore suggest a joint graphical model for date selection. Even unsupervised versions of this model perform as well as supervised state-of-theart approaches. With parameter tuning on training data, it outperforms prior supervised models by a considerable margin.
Giang Binh Tran, Eelco Herder, Katja Markert
Added 13 Apr 2016
Updated 13 Apr 2016
Type Journal
Year 2015
Where ACL
Authors Giang Binh Tran, Eelco Herder, Katja Markert
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