Building a Recommender for Implicit Feedback Data
Last Updated on November 6, 2023 by Editorial Team
Author(s): Michał Oleszak
Originally published on Towards AI.
Provide personalized recommendations without knowing your users.
Each recommendation system is different, and some of them are much easier to build than others. Think about Netflix. They know all about each of their movies, have rich personal user data, and an abundance of user-produced data: plays, ratings, watch time, and so on. In this data-rich environment, one can be sure that the available data contains information needed to produce a good model. Sometimes, however, we don’t have much data about our users or products. Here is what to do in those cases.
The setting in which there is no data available to describe our users, our products, or… Read the full blog for free on Medium.
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Published via Towards AI