DC-NMF: nonnegative matrix factorization based on divide-and-conquer for fast clustering and topic modeling
type: Item
instance of: scholarly article
title: DC-NMF: nonnegative matrix factorization based on divide-and-conquer for fast clustering and topic modeling
zbMATH Open document ID: 1379.90025
author: Rundong Du
author: Da Kuang
author: Barry Drake
author: Haesun Park
published in: Journal of Global Optimization
publication date: 2017-11-02T00:00:00Z
Mathematics Subject Classification ID: 90C26
Mathematics Subject Classification ID: 15A23
zbMATH DE Number: 6802514
zbMATH Keywords: constrained low rank approximation
zbMATH Keywords: nonnegative matrix factorization
zbMATH Keywords: divide and conquer
zbMATH Keywords: clustering
zbMATH Keywords: topic modeling
zbMATH Keywords: text analysis
zbMATH Keywords: scalable algorithms
describes a project that uses: RCV1
describes a project that uses: HierNMF2
describes a project that uses: CLUTO
describes a project that uses: MALLET
describes a project that uses: SmallK
describes a project that uses: SymNMF
MaRDI profile type: Publication
full work available at URL: s10898-017-0515-z
OpenAlex ID: W2605123798
Wikidata QID: Q125911372
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DOI: 10.1007/S10898-017-0515-Z
description: scientific article; zbMATH DE number 6802514