The size increment of online TV's video repositories, rises the necessity of an effective automated video content-based retrieval service. Our project will give a partial answer to that problem by developing a semi-automated tool for characterizing broadcast news video files. Our tool will be constituted of two sections. In the first section, the repositories' video files will be separated from their audio content. Then the audio content will be characterized by a classification system in two predefined categories,: news and sports. In the second section the audio files will be described using proper description languages such as NewsML and SportsML, thus characterizing the initial video file they came from. The effectiveness of our semi-automated tool will be tested in a local repository of news video files, created by a customizable, focuses on video files, data mining web crawler.
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Asonitis, S., Boundas, D., Bokos, G., Poulos, M. (2009). Semi – automated tool for characterizing news video files, using metadata schemas. In: Sicilia, MA., Lytras, M.D. (eds) Metadata and Semantics. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-77745-0_16
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DOI: https://doi.org/10.1007/978-0-387-77745-0_16
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