A novel multi-view clustering approach via proximity-based factorization targeting structural maintenance and sparsity challenges for text and image categorization-Reference-Cited by-同舟云学术

A novel multi-view clustering approach via proximity-based factorization targeting structural maintenance and sparsity challenges for text and image categorization

Published:2021-07 Issue:4 Volume:58 Page:102546
ISSN:0306-4573
Container-title:Information Processing & Management
language:en
Short-container-title:Information Processing & Management

Author:

Bansal Monika^ORCID,Sharma Dolly^ORCID

Publisher

Elsevier BV

Subject

Library and Information Sciences,Management Science and Operations Research,Computer Science Applications,Media Technology,Information Systems

Reference53 articles.

1. Learning from multiple partially observed views - an application to multilingual text categorization;Amini,2009

2. Multi-view clustering;Bickel,2004

3. Graph regularized nonnegative matrix factorization for data representation;Cai;IEEE Transactions on Pattern Analysis and Machine Intelligence,2011

4. Multi-view K-means clustering on big data;Cai,2013

5. GraRep: Learning Graph representations with global structural information;Cao,2015

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