What is data sparsity and why is it a major challenge in data mining?

Data sparsity occurs when datasets contain mostly missing or zero-valued features.

In high-dimensional datasets, especially in recommendation systems and text mining, most feature values are zero. This sparsity makes similarity computation unreliable and reduces the effectiveness of statistical learning methods. Techniques like matrix factorization and embeddings are used to address sparsity.