Collaborative filtering based on nonnegative/binary matrix factorization

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...

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Bibliographic Details
Main Authors:	Yukino Terui, Yuka Inoue, Yohei Hamakawa, Kosuke Tatsumura, Kazue Kudo
Format:	Article
Language:	English
Published:	Frontiers Media S.A. 2025-07-01
Series:	Frontiers in Big Data
Subjects:	Ising machine low-latency collaborative filtering nonnegative/binary matrix factorization combinatorial optimization
Online Access:	https://www.frontiersin.org/articles/10.3389/fdata.2025.1599704/full
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Collaborative filtering based on nonnegative/binary matrix factorization

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