7 Context-aware and hybrid recommendations
This chapter covers
- How to implement a recommendation engine that takes into account the user’s context
- How to design graph models for context-aware recommendation engines
- How to import existing datasets into the graph models designed
- How to combine multiple recommendation approaches
This chapter introduces into the recommendation scenario another variable that the previous approaches ignored: context. The specific conditions in which the user expresses a desire, preference, or need have a strong influence on their behavior and expectations. Different techniques exist to consider the user’s context during the recommendation process. We’ll cover the main ones in this chapter.
Furthermore, to complete our overview of recommendation engine models and algorithms, we’ll see how it’s possible to use a hybrid approach that combines the different types of systems presented so far. Such an approach will enable us to create a unique and powerful recommendation ecosystem capable of overcoming all the issues, limitations, and drawbacks of each individual recommendation method.