[[推荐系统]](Recommender systems)中,SVD用于预测用户对项目的评分。<ref>{{citation | last1=Sarwar | first1=Badrul | last2=Karypis | first2=George | last3=Konstan | first3=Joseph A. | last4=Riedl | first4=John T. | date=2000 |url=https://files.grouplens.org/papers/webKDD00.pdf| title="Application of Dimensionality Reduction in Recommender System – A Case Study" | publisher=University of Minnesota}}</ref>为了在商品机器集群上高效计算SVD,研究人员开发了分布式算法。<ref>{{citation | last1=Bosagh Zadeh | first1=Reza | last2=Carlsson | first2=Gunnar | date=2013 |url=https://stanford.edu/~rezab/papers/dimsum.pdf| title="Dimension Independent Matrix Square Using MapReduce" | arxiv=1304.1467 | bibcode=2013arXiv1304.1467B}}</ref> | [[推荐系统]](Recommender systems)中,SVD用于预测用户对项目的评分。<ref>{{citation | last1=Sarwar | first1=Badrul | last2=Karypis | first2=George | last3=Konstan | first3=Joseph A. | last4=Riedl | first4=John T. | date=2000 |url=https://files.grouplens.org/papers/webKDD00.pdf| title="Application of Dimensionality Reduction in Recommender System – A Case Study" | publisher=University of Minnesota}}</ref>为了在商品机器集群上高效计算SVD,研究人员开发了分布式算法。<ref>{{citation | last1=Bosagh Zadeh | first1=Reza | last2=Carlsson | first2=Gunnar | date=2013 |url=https://stanford.edu/~rezab/papers/dimsum.pdf| title="Dimension Independent Matrix Square Using MapReduce" | arxiv=1304.1467 | bibcode=2013arXiv1304.1467B}}</ref> |