A matrix factorization framework for jointly analyzing multiple nonnegative data

A matrix factorization framework for jointly analyzing multiple nonnegative data

Nonnegative matrix factorization based methods provide one of the simplest and most effective approaches to text mining. However, their applicability is mainly limited to analyzing a single data source. In this paper, we propose a novel joint matrix factorization framework which can jointly analyze...

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Bibliographic Details
Main Authors: Gupta, Sunil, Phung, Dinh, Adams, Brett, Venkatesh, Svetha
Other Authors: Michael W. Berry
Format: Conference Paper
Published: Omnipress 2011
Online Access:http://hdl.handle.net/20.500.11937/16617

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