to download project abstract

In terms of e-commerce, recommender framework for the most part guides
customers in a customized manner towards interesting / customized manner
towards products in a large space of feasible options. To provide reliable
recommendation, the recommender systems need to capture the exact customer’s
need and preference into a user profile. However, for complexes products/
services such as movies, music, news, user emotions play surprisingly critical
roles in the decision making process. The traditional method of user profile system
doesn’t consider the impact of user emotion, the recommender systems cannot
understand and capture the continually developing inclinations of a user. The
Movie recommendation is based on notions with regards to a client ‘ s emotions
and inclinations. This project additionally examines the System architecture and its
implementation, as well as its evaluation procedure. We believe that our system
provides improved recommendation to users because it enables the users to
understand the relation between their emotional states and the recommended

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