  Robust Trust Reputation Systems (TRS) provide a most trustful reputation
score for a specific product or service so as to support relying parties taking
the right decision while interacting with an e-commerce application. Thus, TRS
must rely on an appropriate architecture and suitable algorithms that are able
to improve the selection, storage, generation and classification of textual
feedbacks. In this work, we propose a new architecture for TRS in e-commerce
applications. In fact, we propose an intelligent layer which displays to each
feedback provider, who has already given his recommendation on a product, a
collection of prefabricated feedbacks related to the same product. The proposed
reputation algorithm generates better trust degree of the user, trust degree of
the feedback and a better global reputation score of the product.
