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This paper presents a novel method for automatically detecting and tracking news topics from multimodal TV news data. We propose a multimodal topic and-or graph (MT-AOG) to jointly represent textual and visual elements of news stories and their latent topic structures. An MT-AOG leverages a context-sensitive grammar that can describe the hierarchical composition of news topics by semantic elements...
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