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What’s New? Analysing Language-Specific Wikipedia Entity Contexts to Support Entity-Centric News Retrieval

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Book cover Transactions on Computational Collective Intelligence XXVI

Part of the book series: Lecture Notes in Computer Science ((TCCI,volume 10190))

Abstract

Representation of influential entities, such as celebrities and multinational corporations on the web can vary across languages, reflecting language-specific entity aspects, as well as divergent views on these entities in different communities. An important source of multilingual background knowledge about influential entities is Wikipedia—an online community-created encyclopaedia—containing more than 280 language editions. Such language-specific information could be applied in entity-centric information retrieval applications, in which users utilise very simple queries, mostly just the entity names, for the relevant documents. In this article we focus on the problem of creating language-specific entity contexts to support entity-centric, language-specific information retrieval applications. First, we discuss alternative ways such contexts can be built, including Graph-based and Article-based approaches. Second, we analyse the similarities and the differences in these contexts in a case study including 219 entities and five Wikipedia language editions. Third, we propose a context-based entity-centric information retrieval model that maps documents to aspect space, and apply language-specific entity contexts to perform query expansion. Last, we perform a case study to demonstrate the impact of this model in a news retrieval application. Our study illustrates that the proposed model can effectively improve the recall of entity-centric information retrieval while keeping high precision, and provide language-specific results.

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Notes

  1. 1.

    http://en.wikipedia.org/wiki/List_of_Wikipedias.

  2. 2.

    http://www.dw.com/en/.

  3. 3.

    http://www.spiegel.de/international/.

  4. 4.

    http://www.thelocal.de/.

  5. 5.

    http://www.theguardian.com/.

  6. 6.

    http://www.express.co.uk/.

  7. 7.

    The annotated datasets are accessible at: https://github.com/zhouyiwei/WIKIIRDATA.

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Acknowledgments

This work was partially funded by the COST Action IC1302 (KEYSTONE), the ERC under ALEXANDRIA (ERC 339233) and H2020-MSCA-ITN-2014 WDAqua (64279).

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Warwick, Coventry, UK

    Yiwei Zhou & Alexandra I. Cristea

  2. University of Southampton, Southampton, UK

    Elena Demidova

  3. L3S Research Center, Hannover, Germany

    Elena Demidova

Authors
  1. Yiwei Zhou
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  2. Elena Demidova
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  3. Alexandra I. Cristea
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Corresponding authors

Correspondence to Yiwei Zhou or Alexandra I. Cristea .

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Editors and Affiliations

  1. Institute of Informatics, Wroclaw University of Technology, Wroclaw, Poland

    Ngoc Thanh Nguyen

  2. Swinburne University of Technology , Hawthorn, South Australia, Australia

    Ryszard Kowalczyk

  3. University of Lisbon , Lisbon, Portugal

    Alexandre Miguel Pinto

  4. Huawei German Research Center, Munich, Germany

    Jorge Cardoso

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Zhou, Y., Demidova, E., Cristea, A.I. (2017). What’s New? Analysing Language-Specific Wikipedia Entity Contexts to Support Entity-Centric News Retrieval. In: Nguyen, N., Kowalczyk, R., Pinto, A., Cardoso, J. (eds) Transactions on Computational Collective Intelligence XXVI. Lecture Notes in Computer Science(), vol 10190. Springer, Cham. https://doi.org/10.1007/978-3-319-59268-8_10

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  • DOI: https://doi.org/10.1007/978-3-319-59268-8_10

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