Skip to main content

Research Repository

Advanced Search

What's new? Analysing language-specific Wikipedia entity contexts to support entity-centric news retrieval

Zhou, Yiwei; Demidova, Elena; Cristea, A.I.

What's new? Analysing language-specific Wikipedia entity contexts to support entity-centric news retrieval Thumbnail


Authors

Yiwei Zhou

Elena Demidova



Contributors

N. Nguyen
Editor

R. Kowalczyk
Editor

A. Pinto
Editor

J. Cardoso
Editor

Abstract

Representation of influential entities, such as celebrities and multinational corporations on the web can vary across languages, re- flecting 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 languagespecific 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 220 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 languagespecific 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.

Citation

Zhou, Y., Demidova, E., & Cristea, A. (2017). What's new? Analysing language-specific Wikipedia entity contexts to support entity-centric news retrieval. In N. Nguyen, R. Kowalczyk, A. Pinto, & J. Cardoso (Eds.), Transactions on Computational Collective Intelligence XXVI (2010-231). Springer Verlag. https://doi.org/10.1007/978-3-319-59268-8_10

Acceptance Date Oct 7, 2017
Online Publication Date Jun 15, 2017
Publication Date Jun 15, 2017
Deposit Date Jul 11, 2018
Publicly Available Date Mar 29, 2024
Publisher Springer Verlag
Pages 2010-231
Series Title Lecture notes in computer science
Series Number 10190
Book Title Transactions on Computational Collective Intelligence XXVI.
ISBN 9783319592671
DOI https://doi.org/10.1007/978-3-319-59268-8_10
Related Public URLs http://wrap.warwick.ac.uk/85950/

Files





You might also like



Downloadable Citations