NobleBlocks
Public

Collaborative filtering based on nonnegative/binary matrix factorization

Published in arXiv (Cornell University) • Oct 14, 2024
NobleIDNI7P85W89R30S66
Authors:
Yukino Terui
,
Yukari Inoue
,
Yohei Hamakawa

Abstract

Collaborative filtering generates recommendations by exploiting user-item similarities based on rating data, which often contains numerous unrated items. To predict scores for unrated items, matrix factorization techniques such as nonnegative matrix factorization (NMF) are often employed. Nonnegativ...

Finding related papers...

Discussions

(0)

No comments yet

Be the first to share your thoughts!