A new text clustering approach based on non-negative matrix factorization is presented.
提出一种基于非负矩阵分解的文本聚类方法。
参考来源 - 基于NMF的文本聚类方法 in C·2,447,543篇论文数据,部分数据来源于NoteExpress
Sounds like a classic matrix factorization task to me.
听起来像是一个经典的矩阵分解我的任务。
An algorithm with regularization constrains for nonnegative matrix factorization (RCNMF) is proposed.
提出一种带有正则约束的非负矩阵分解算法(RCNMF)。
The matrix factorization and its modification is one of the most effective techniques in numerical linear algebra.
矩阵分解的校正技术是数值线性代数中最有效的工具之一。
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