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Event Detection for Heterogeneous News Streams

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Natural Language Processing and Information Systems (NLDB 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10260))

Abstract

In this paper we tackle the problem of detecting events from multiple and heterogeneous streams of news. In particular, we focus on news which are heterogeneous in length and writing styles since they are published on different platforms (i.e., Twitter, RSS portals, and news websites). This heterogeneity makes the event detection task more challenging, hence we propose an approach able to cope with heterogeneous streams of news. Our technique combines topic modeling, named-entity recognition, and temporal analysis to effectively detect events from news streams. The experimental results confirmed that our approach is able to better detect events than other state-of-the-art techniques and to divide the news in high-precision clusters based on the events they describe.

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Notes

  1. 1.

    The words channel and stream are used interchangeably in this paper, and we use the general term news to refer to a news article, an RSS feed, or a tweet.

  2. 2.

    https://www.crowdflower.com/.

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Acknowledgement

This research was partially funded by the Secrétariat d’Etat à la formation, à la recherche et à l’innovation (SEFRI) under the project AHTOM (Asynchronous and Heterogeneous TOpic Mining).

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Authors and Affiliations

  1. Faculty of Informatics, Università della Svizzera Italiana, Lugano, Switzerland

    Ida Mele & Fabio Crestani

Authors
  1. Ida Mele
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  2. Fabio Crestani
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Corresponding author

Correspondence to Ida Mele .

Editor information

Editors and Affiliations

  1. Erasmus University Rotterdam, Rotterdam, The Netherlands

    Flavius Frasincar

  2. University of Liège , Liège, Belgium

    Ashwin Ittoo

  3. Japan Advanced Institute of Science and Technology, Nomi, Japan

    Le Minh Nguyen

  4. Conservatoire National des Arts et Métiers, Paris, France

    Elisabeth Métais

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Mele, I., Crestani, F. (2017). Event Detection for Heterogeneous News Streams. In: Frasincar, F., Ittoo, A., Nguyen, L., Métais, E. (eds) Natural Language Processing and Information Systems. NLDB 2017. Lecture Notes in Computer Science(), vol 10260. Springer, Cham. https://doi.org/10.1007/978-3-319-59569-6_11

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  • DOI: https://doi.org/10.1007/978-3-319-59569-6_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59568-9

  • Online ISBN: 978-3-319-59569-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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