2015 | OriginalPaper | Buchkapitel
Timeline Summarization from Relevant Headlines
verfasst von : Giang Tran, Mohammad Alrifai, Eelco Herder
Erschienen in: Advances in Information Retrieval
Verlag: Springer International Publishing
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Timeline summaries are an effective way for helping newspaper readers to keep track of long-lasting news stories, such as the Egypt revolution. A good timeline summary provides a concise description of only the main events, while maintaining good understandability. As manual construction of timelines is very time-consuming, there is a need for automatic approaches. However, automatic selection of relevant events is challenging due to the large amount of news articles published every day. Furthermore, current state-of-the-art systems produce summaries that are suboptimal in terms of relevance and understandability. We present a new approach that exploits the headlines of online news articles instead of the articles’ full text. The quantitative and qualitative results from our user studies confirm that our method outperforms state-of-the-art system in these aspects.