Building a hybrid recommendation system for Jokes recommendations

We see that both content-based filtering and collaborative filtering have their strengths and weaknesses. To overcome the issues, organizations build recommender systems that combine two or more technique and they are termed hybrid recommendation models. An example of this is a combination of content-based, IBCF, UBCF, and model-based recommender engine. This takes into account all the possible aspects that contribute to making the most relevant recommendation to the user. The following diagram shows an example approach followed in hybrid recommendation engines:

Sample approach ...

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