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—This paper presents a solution to extend the IEEE LOM standard with ontology-based semantic annotations for efficient use of learning objects outside Learning Management Systems. The data model corresponding to this approach is first presented. The proposed indexing technique for this model development in order to acquire a better annotation of learning(More)
Nowadays, social networks are more and more widely used as a solution for enriching users’ profiles in systems such as recommender systems or personalized systems. For an unknown user’s interest, the user’s social network can be a meaningful data source for deriving that interest. However, in the literature very few techniques are designed to meet this(More)
A recent trend in multimedia information retrieval systems is the integration of users, by their preferences and interests, in the retrieval process. Generally, such systems consider the user only after the query's execution, while the results' presentation. We propose to consider the user as a source of metadata, by exploiting his behaviour and to enrich(More)
Metadata on multimedia documents may help to describe their content and make their processing easier, for example by identifying events in temporal media, as well as carrying descriptive information for the overall resource. Metadata is essentially static and may be associated with, or embedded in, the multimedia contents. The aim of this paper is to(More)
This paper presents a solution for recommending documents to students according to their current activity that is tracked in terms of semantic annotations associated to the accessed resources. Our approach is based on an existing tracking system that captures the user current activity, which is extended to build a user profile that comprises his/her(More)