Searching news articles using an event knowledge graph leveraged by Wikidata

Rudnik, Charlotte; Ehrhart, Thibault; Ferret, Olivier; Teyssou, Denis; Troncy, Raphaël; Tannier, Xavier
WWW 2019, The Web Conference 2019, 30th International World Wide Web Conference, 13-17 May 2019, San Francisco, USA

News agencies produce thousands of multimedia stories describing events happening in the world that are either scheduled such as sports competitions, political summits and elections, or breaking events such as military conflicts, terrorist attacks, natural disasters, etc. When writing up those stories, journalists refer to contextual background and to compare with past similar events. However, searching for precise facts described in stories is hard. In this paper, we propose a general method that leverages the Wikidata knowledge base to produce semantic annotations of news articles. Next, we describe a semantic search engine that supports both keyword based search in news articles and structured data search providing filters for properties belonging to specific event schemas that are automatically inferred.


DOI
HAL
Type:
Conference
City:
San Francisco
Date:
2019-05-13
Department:
Data Science
Eurecom Ref:
5860
Copyright:
© ACM, 2019. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in WWW 2019, The Web Conference 2019, 30th International World Wide Web Conference, 13-17 May 2019, San Francisco, USA http://dx.doi.org/10.1145/3308560.3316761

PERMALINK : https://www.eurecom.fr/publication/5860