Adaptive Representation Of Digital Resources Search Results In Personal Learning Environment

The massive explosion of digital resources available in the user's personal environment creates many issues. Users aim to select among a mass of heterogeneous digital resources, the best one to use in the activity. Traditionally, this process is time consuming and requires a lot of effort for the user to optimize selecting parameters. That often makes unexploitable digital resources available in repositories or digital libraries. In this paper, we proposed an approach that allows a user to have new ways of interpreting the resource search results. We proposed a method for adaptive visual representation of these results based on the context of use and the user profile. This approach use an adaptive tf-idf scoring and adaptive visual representation to allow relevant digital resources selection. This study was conducted as part of the design of a personal environment for consolidated digital resource management called PRISE (PeRsonal Interactive research Smart Environment).