Integration by Matrix Factorization (IMF) is an unsupervised algorithm for combining information from related views, using a late integration strategy. Combination is performed by applying an approach based on matrix factorization to group related clusters produced on individual views. This yields a projection of the original clusters in the form of a new set of "meta-clusters" covering the entire domain. 

Relevant Publications

D. Greene and P. Cunningham. "A matrix factorization approach for integrating multiple data views". In Proc. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD’09), 2009. [PDF] [BibTeX]

Relevant Datasets

3Sources Collection 

A multi-view text corpus, constructed from news articles from three online news services.

Synthetic Multi-view Datasets 

BBC Datasets