What are the common challenges faced in recommender systems?

What are the common challenges faced in recommender systems?

Some common challenges include data sparsity, cold start problems, and scalability issues.

Can you explain what data sparsity means?

Data sparsity refers to the lack of sufficient user-item interactions, making it hard to generate accurate recommendations.

What is the cold start problem?

The cold start problem occurs when a system has little to no data about new users or items, hindering effective recommendations.

How can these challenges be addressed?

Techniques like collaborative filtering, content-based filtering, and hybrid models can help mitigate these challenges.