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Leveraging Semantic Annotations to Link Wikipedia and News Archives

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons79375

Mishra,  Arunav
Databases and Information Systems, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons44119

Berberich,  Klaus
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Fulltext (public)

MPI-I-2016-5-002.pdf
(Any fulltext), 339KB

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Citation

Mishra, A., & Berberich, K.(2016). Leveraging Semantic Annotations to Link Wikipedia and News Archives (MPI-I-2016-5-002). Saarbrücken: Max-Planck-Institut für Informatik.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0029-5FF0-A
Abstract
The incomprehensible amount of information available online has made it difficult to retrospect on past events. We propose a novel linking problem to connect excerpts from Wikipedia summarizing events to online news articles elaborating on them. To address the linking problem, we cast it into an information retrieval task by treating a given excerpt as a user query with the goal to retrieve a ranked list of relevant news articles. We find that Wikipedia excerpts often come with additional semantics, in their textual descriptions, representing the time, geolocations, and named entities involved in the event. Our retrieval model leverages text and semantic annotations as different dimensions of an event by estimating independent query models to rank documents. In our experiments on two datasets, we compare methods that consider different combinations of dimensions and find that the approach that leverages all dimensions suits our problem best.