Exploring the basic intuition behind the recommendation engines.
Recommendation Engines are the programs which basically compute the similarities between two entities and on that basis, they give us the targeted output. If we look at the root of any recommendation engine, they all are trying to find out the amount of similarity between two entities. Then, the computed similarities can be used to deduce various kinds of recommendations and relationships between them. Recommendation Engines are mostly based on the following techniques:
- Popularity Based Filtering.
- Collaborative Filtering (User Based / Item Based).
- Hybrid User-Item Based Collaborative Filtering.
- Content Based Filtering.