We introduce a new recommending paradigm based on the genomic features of the candidate objects. The system is based on the tree structure of the object metadata which we convert in acceptance rules, leaving the user the discretion of selecting the most convincing rules for her/his scope. We framed the deriving recommendation system on a content management platform within the scope of the European Project NETT and tested it on the Entree UCI benchmark.
CITATION STYLE
Apolloni, B., Bassis, S., Mesiti, M., Valtolina, S., & Epifania, F. (2016). A rule based recommender system. In Smart Innovation, Systems and Technologies (Vol. 54, pp. 87–96). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-319-33747-0_9
Mendeley helps you to discover research relevant for your work.