Abstract: Recommender systems are essential in digital services for helping users find relevant items. One of the main challenges faced by these systems is the problem of sparsity, where limited ...

Abstract: Real-time movie recommendation systems must efficiently handle large amounts of sparse user-item interaction data while maintaining great prediction accuracy. Conventional collaborative ...

High-performance Python library for text factorization using compressed suffix trees. The library provides efficient algorithms for finding non-overlapping factors in text data, with both in-memory ...