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.
A rule based recommender system / B. Apolloni, S. Bassis, M. Mesiti, S. Valtolina, F. Epifania - In: Advances in neural networks : computational Intelligence for ICT / [a cura di] S. Bassis, A. Esposito, F.C. Morabito, E. Pasero. - [s.l] : Springer Science, 2016. - ISBN 9783319337463. - pp. 87-96 (( convegno WIRN tenutosi a Vietri sul mare nel 2015.
A rule based recommender system
B. ApolloniPrimo
;S. Bassis
;M. Mesiti;S. ValtolinaPenultimo
;F. EpifaniaUltimo
2016
Abstract
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.
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