Dependency

Recommender systems

In this lesson, we will build a movie recommender system and add some logic to it. A recommender system is a system that filters some entities based on the user’s history. Recommender systems also rank these items based on user preferences. The system works by taking an input and then finding items similar to that input.

In this lesson, we will write the basic code for a movie recommender application. The application will take a movie and recommend other movies similar to it. There are various ways in which recommendations can be found. One method is content-based filtering in which item-to-item similarity is used as a basis for finding matches. So, for a movie like Finding Dory, the system will find movies of the same genre, like Happy Feet, Ice Age, Shark Tale, etc.

We will create sub-packages inside the io.datajek.spring.basics.movierecommendersystem package to keep the files for every lesson separate. This is an optional step. Right-click on the base package and click "New" → "Package". Then provide the name as lesson1 and ...