Deep Collaborative Filtering using two stage information Retrieval

The company wants to develop a state of art recommendation system for the clients. A recommendation system is a piece of software that provides products’ suggestions to customers on a website. For example the products suggestions that can be seen on Amazon’s web page are generated by its recommendation engine.
The typical recommendation engines work by utilizing the existing user-product preferences information. They recommend products to a user by comparing his preferences to other similar users’ preferences. The typical example of this is Users who bought item-A also bought item-B.

Recommender Model Development

Popular content-driven websites like YouTube, Vimeo and Soundcloud receive a large amount of content annually and are visited by billions of users world-wide. However, the majority of the content on these sites has little to no structure. For example, many videos on YouTube are only found in the personal playlists and have virtually no user interaction or content data. Consequently, while many of these videos could be of high interest to the YouTubes community, a lack of reliable information makes it very difficult for recommender systems to surface them.