Linking Multimedia Content for Efficient News Browsing

Abstract

As the amount of news information available online grows, media professionals are in need of advanced tools to explore the information surrounding speci c 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 o er 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. ese 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 e cient 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 signi cant improvement compared to classical search engines.

Multimedia Analytics Challenges and Opportunities for Creating Interactive Radio Content

“…The requirements for handling large amounts of heterogeneous multimedia data in order to enable creators to efficiently produce richer content makes this a multimedia analytics problem. Despite this, very few papers dealing with multimedia analytics actually address radio content (beyond mentioning the word radio in the introduction); see, for example, [26] and [10].…”