Other frequently used recommendation methods
We have discussed the market basket analysis and collaborative filtering in depth for building personalized recommendation systems. However, there are various other ways these recommendation systems can be built. As previously mentioned, some of the common AI/ML-based approaches are association rules and collaborative filtering algorithms, which we have covered in this chapter; predictive modeling approaches are often used as well, and nowadays a hybrid of all these approaches is a typical method of building more comprehensive recommendation systems.
Not only are there AI/ML-driven approaches for recommendation systems but there can be various other ways to recommend products or content without even using AI/ML. The following are some common methods used for making recommendations:
- Bestsellers or top views: As the name suggests, recommendations based on the bestselling products or the most frequently viewed content are still...
