2005 | OriginalPaper | Chapter
RitroveRAI: A Web Application for Semantic Indexing and Hyperlinking of Multimedia News
Authors : Roberto Basili, Marco Cammisa, Emanuale Donati
Published in: The Semantic Web – ISWC 2005
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
In this paper, a system, RitroveRAI, addressing the general problem of enriching a multimedia news stream with semantic metadata is presented. News metadata here are explicitly derived from transcribed sentences or implicitly expressed into a topical category automatically detected. The enrichment process is accomplished by searching the same news expressed by different agencies reachable over the Web. Metadata extraction from the alternative sources (i.e. Web pages) is similarly applied and finally integration of the sources (according to some heuristic of pertinence) is carried out. Performance evaluation of the current system prototype has been carried out on a large scale. It confirms the viability of the RitroveRAI approach for realistic (i.e. 24 hours) applications and continuous monitoring and metadata extraction from multimedia news data.