Justification of recommendations increases trust between users and the system but also
generates more relevant recommendations than recommendation systems that do not
incorporate it. That is why, we conducted a justification study of the recommendation for IAAS.
Our comparative study shows that IAAS, which currently does not offer the opportunity to justify
recommendations, needs to be improved. From the analysis of justification methods studied in
this work, it appears that none of these methods can be used effectively in IAAS. That is why, we
proposed a new IAAS architecture that deals separately with item classification and the
extraction of the justification has added the item during recommendation generation. The item
selection method remains unchanged as we plan to implement a new strategy to filter user’s
reviews should now be extended to four elements: the documentary unit, the group of users, the
justification and the weight. Opinion A=(UD,G,J,a). Where UD represents the documentary
unit, G the user group, J is the justification and a is the weight of the recommendation.
IAAS, Justification in Recommender Systems, users reviews, weight of reviews.