User Trace-Based Recommendation System for a Digital Archive
Résumé
Precious collections of cultural heritage documents are available for study on the internet via web archives. The automatically added metadata on these scanned documents are not sufficient to make a specific search. User effort is needed to add manual annotations in order to enhance document content accessibility and exploitability. Annotators have different experiences in dissimilar document domains. Hence the reuse of users’ experiences is constructive to accelerate the annotation process and to correct user mistakes. In this article we present our digital archive model and a prototype to collaboratively annotate online ancient manuscripts. Our system tracks important user actions and saves them as traces composed of hierarchical episodes. These episodes are considered as cases to be reused by a recommender system.