What is data sparsity in recommender systems?

What is data sparsity in recommender systems?

Data sparsity refers to the lack of sufficient data points in a dataset, which can hinder the performance of recommender systems.

Why is data sparsity a problem for recommendations?

It makes it difficult for the system to identify patterns and preferences, leading to less accurate recommendations.

How can we mitigate data sparsity?

Techniques like collaborative filtering, content-based filtering, and hybrid methods can help address data sparsity.

Can you give an example of a hybrid method?

Sure! A hybrid method combines collaborative filtering and content-based filtering to leverage the strengths of both approaches.