Creating an Intelligent Recommendation System
Now that we have loaded the data into a graph, and looked at how we can augment the graph using Langchain4j and Spring AI, along with generating recommendations, we will look at how we can go further to improve the recommendations by leveraging Graph Data Science (GDS) algorithms and machine learning. We will review the GDS algorithms provided by Neo4j to go beyond the recommendation system we created in the previous chapter. We will also learn how to use the GDS algorithms to build collaborative filtering as well as content-based approaches to provide recommendations. We will also take a look at the results after we run the algorithms to review how our approach is working and whether we are on the right path to build a better recommendation system. We will try to understand why these algorithms are better than the approach we implemented in the previous chapter.
In this chapter, we are going to cover the following main topics:
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