User-Specific Bicluster-based Collaborative Filtering: Handling Preference Locality, Sparsity and Subjectivity. (arXiv:2211.08366v1 [cs.IR])

Collaborative Filtering (CF), the most common approach to build Recommender
Systems, became pervasive in our daily lives as consumers of products and
services. However, challenges limit the effectiveness of Collaborative
Filtering approaches when dealing with recommendation data, mainly due to the
diversity and locality of user preferences, structural sparsity of user-item
ratings, subjectivity of rating scales, and increasingly high item
dimensionality and user bases. To answer some of these challenges, some authors
proposed successful approaches combining CF with Biclustering techniques. …

arxiv collaborative collaborative filtering filtering sparsity