Managing and querying efficiently distributed semantic multimedia metadata collections
Résumé
Currently, many multimedia contents are acquired and stored in real time and on different locations. In order to retrieve efficiently the desired information and to avoid centralizing all metadata, we propose to compute a centralized metadata resume, i.e., a concise version of the whole metadata, which locates some desired multimedia contents on remote servers. The originality of this resume is that it is automatically constructed based on the extracted metadata. In this paper, we present a method to construct such resume and illustrate our framework with current Semantic Web technologies, such as RDF and SPARQL for representing and querying semantic metadata. Some experimental results are provided in order to show the benefits of indexing and retrieving multimedia contents without centralizing multimedia contents or their associated metadata, and to prove the efficiency of a metadata resume.