Semantic recommender system for the recovery of the preserved web heritage

This paper presents a prototype of a semantic personalized recommender system for a repository of preserved web files. To do this, we design and implement a semantic repository of preserved web files, containing metadata associated with each preserved site. The knowledge stored in the metadata of the semantic repository is used for the recommender system, in order to give prioritized recommendations of the different preserved web files (or web heritage) that meet certain search criteria. The proposed recommender also considers semantic associations, in order to recommend not only the websites matched to the search criteria, but also semantically related.