Searching News Articles Using an Event Knowledge Graph Leveraged by Wikidata - Archive ouverte HAL
Conference Papers Year : 2019

Searching News Articles Using an Event Knowledge Graph Leveraged by Wikidata

Abstract

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.
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Dates and versions

hal-02406962 , version 1 (06-05-2024)

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Charlotte Rudnik, Thibault Ehrhart, Olivier Ferret, Denis Teyssou, Raphaël Troncy, et al.. Searching News Articles Using an Event Knowledge Graph Leveraged by Wikidata. Companion The 2019 World Wide Web Conference, May 2019, San Francisco, United States. pp.1232-1239, ⟨10.1145/3308560.3316761⟩. ⟨hal-02406962⟩
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