Abstract
Wikipedia is widely considered the largest and most up-to-date online encyclopedia, with its content being continuously maintained by a supporting community. In many cases, real-life events like new scientific findings, resignations, deaths, or catastrophes serve as triggers for collaborative editing of articles about affected entities such as persons or countries. In this paper, we conduct an in-depth analysis of event-related updates in Wikipedia by examining different indicators for events including language, meta annotations, and update bursts. We then study how these indicators can be employed for automatically detecting event-related updates. Our experiments on event extraction, clustering, and summarization show promising results towards generating entity-specific news tickers and timelines.
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Georgescu, M., Kanhabua, N., Krause, D., Nejdl, W., Siersdorfer, S. (2013). Extracting Event-Related Information from Article Updates in Wikipedia. In: Serdyukov, P., et al. Advances in Information Retrieval. ECIR 2013. Lecture Notes in Computer Science, vol 7814. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36973-5_22
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DOI: https://doi.org/10.1007/978-3-642-36973-5_22
Publisher Name: Springer, Berlin, Heidelberg
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