2013 | OriginalPaper | Buchkapitel
Extracting Event-Related Information from Article Updates in Wikipedia
verfasst von : Mihai Georgescu, Nattiya Kanhabua, Daniel Krause, Wolfgang Nejdl, Stefan Siersdorfer
Erschienen in: Advances in Information Retrieval
Verlag: Springer Berlin Heidelberg
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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.