Linking Multimedia Content for Efficient News Browsing
Authors: 
Rémi Bois, Guillaume Gravier, Éric Jamet, Emmanuel Morin, Maxime Robert, Pascale SébillotAuthors Info & Claims
Pages 301 - 307
Abstract
As the amount of news information available online grows, media are in need of advanced tools to explore the information surrounding specific events before writing their own piece of news, e.g., adding context and insight. While many tools exist to extract information from large datasets, they do not offer an easy way to gain insight from a news collection by browsing, going from article to article and viewing unaltered original content. Such browsing tools require the creation of rich underlying structures such as graph representations. These representations can be further enhanced by typing links that connect nodes, in order to inform the user on the nature of their relation. In this article, we introduce an efficient way to generate links between news items in order to obtain an easily navigable graph, and enrich this graph by automatically typing created links. User evaluations are conducted on real world data in order to assess for the interest of both the graph representation and link typing in a press reviewing task, showing a significant improvement compared to classical search engines.
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Index Terms
- Linking Multimedia Content for Efficient News Browsing
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Published In
June 2017
524 pages
ISBN:9781450347013
DOI:10.1145/3078971
- General Chairs:
- Bogdan Ionescu,
- Nicu Sebe,
- Program Chairs:
- Jiashi Feng,
- Martha Larson,
- Rainer Lienhart,
- Cees Snoek
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Published: 06 June 2017
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