MM13:structurednews

Brendan Jou, Hongzhi Li, Joseph G. Ellis, Daniel Morozoff, Shih-Fu Chang. Structured Exploration of Who, What, When, and Where in Heterogeneous Multimedia News Sources. In ACM Multimedia, Grand Challenge, October 2013.

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Abstract

We present a fully automatic system from raw data gathering to navigation over heterogeneous news sources, including over 18k hours of broadcast video news, 3.58M online articles, and 430M public Twitter messages. Our system addresses the challenge of extracting "who," "what," "when," and "where" from a truly multimodal perspective, leveraging audiovisual information in broadcast news and those embedded in articles, as well as textual cues in both closed captions and raw document content in articles and social media. Performed over time, we are able to extract and study the trend of topics in the news and detect interesting peaks in news coverage over the life of the topic. We visualize these peaks in trending news topics using automatically extracted keywords and iconic images, and introduce a novel multimodal algorithm for naming speakers in the news. We also present several intuitive navigation interfaces for interacting with these complex topic structures over different news sources

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Brendan Jou
Hongzhi Li
Joseph Ellis
Shih-Fu Chang

BibTex Reference

@InProceedings{MM13:structurednews,
   Author = {Jou, Brendan and Li, Hongzhi and Ellis, Joseph G. and Morozoff, Daniel and Chang, Shih-Fu},
   Title = {Structured Exploration of Who, What, When, and Where in Heterogeneous Multimedia News Sources},
   BookTitle = {ACM Multimedia},
   Series = {Grand Challenge},
   Month = {October},
   Year = {2013}
}

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