کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
416598 681388 2007 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Algorithms and applications for approximate nonnegative matrix factorization
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Algorithms and applications for approximate nonnegative matrix factorization
چکیده انگلیسی

The development and use of low-rank approximate nonnegative matrix factorization (NMF) algorithms for feature extraction and identification in the fields of text mining and spectral data analysis are presented. The evolution and convergence properties of hybrid methods based on both sparsity and smoothness constraints for the resulting nonnegative matrix factors are discussed. The interpretability of NMF outputs in specific contexts are provided along with opportunities for future work in the modification of NMF algorithms for large-scale and time-varying data sets.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 52, Issue 1, 15 September 2007, Pages 155–173
نویسندگان
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