Hybrid recommender systems

As you have seen, there are several pros and cons of using collaborative filtering and content-based filtering. Therefore, to overcome the limitations of these two approaches, recent trends have shown that a hybrid approach can be more effective and accurate by combining collaborative filtering and content-based filtering. Sometimes, factorization approaches such as MF and Singular Value Decomposition (SVD) are used to make them robust. Hybrid approaches can be implemented in several ways:

  • At first, content-based and collaborative-based predictions are computed separately, and later on we combine them, that is, unification of these two into one model. In this approach, FM and SVD are used extensively.
  • Adding content-based ...

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