Analysing Entity Context in Multilingual Wikipedia to Support Entity-Centric Retrieval Applications

  • Yiwei Zhou
  • Elena Demidova
  • Alexandra I. Cristea
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9398)


Representation of influential entities, such as famous people 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. A systematic analysis of language-specific entity contexts can provide a better overview of the existing aspects and support entity-centric retrieval applications over multilingual Web data. An important source of cross-lingual information about influential entities is Wikipedia — an online community-created encyclopaedia — containing more than 280 language editions. In this paper we focus on the extraction and analysis of the language-specific entity contexts from different Wikipedia language editions over multilingual data. We discuss alternative ways such contexts can be built, including graph-based and article-based contexts. Furthermore, we analyse the similarities and the differences in these contexts in a case study including 80 entities and five Wikipedia language editions.



This work was partially funded by the COST Action IC1302 (KEYSTONE) and the European Research Council under ALEXANDRIA (ERC 339233).


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Copyright information

© Springer International Publishing Switzerland 2015

Open Access This chapter is distributed under the terms of the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Authors and Affiliations

  • Yiwei Zhou
    • 1
  • Elena Demidova
    • 2
  • Alexandra I. Cristea
    • 1
  1. 1.Department of Computer ScienceUniversity of WarwickCoventryUK
  2. 2.L3S Research Center and Leibniz Universität HannoverHannoverGermany

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