Other User's Choice

Alie’s “other user’s choice” recommendations rely on the likes and dislikes of other users. Alie uses collaborative filtering & deep learning, to identify patterns among user actions and compute a similarity index between the users. The similarity index helps in establishing the link between users, which in turn enables Alie to suggest accurate personalized recommendations for every user. For Ex. User A & B have seen a movie named ‘M1’ and they both liked it, if User A watches another movie named ‘M2’ then movie ‘M2’ will be shown as a recommendation to User B.

This algorithm will enable you to recommend items to your end-users that have been purchased, reviewed, or liked by other users having similar tastes & preferences. The performance of the “other user’s choice” algorithm keeps improving as more and more similar users and their choices get discovered in real-time.