Automated semantic structure reconstruction and representation generation for broadcast news

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Abstract
This paper addresses the problem of recovering the semantic structure of broadcast news. A hierarchy of retrievable units is automatically constructed by integrating information from different media. The hierarchy provides a compact, yet meaningful, abstraction of the broadcast news data, similar to a conventional table of content that can serve as an effective index table, facilitating the capability of browsing through large amounts of data in a nonlinear fashion. The recovery of the semantic structure of the data further enables the automated solutions in constructing visual representations that are relevant to the semantics as well as in establishing useful relationships among data units such as topic categorization and content based multimedia hyperlinking. Preliminary experiments of integrating different media for hierarchical segmentation of semantics have yielded encouraging results. Some of the results are presented and discussed in this paper.

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