Multi-layer manifold learning for deep non-negative matrix factorization-based multi-view clustering
Multi-view data clustering based on Non-negative Matrix Factorization (NMF) has been
commonly used for pattern recognition by grouping multi-view high-dimensional data by …
commonly used for pattern recognition by grouping multi-view high-dimensional data by …
Uniform distribution non-negative matrix factorization for multiview clustering
Multiview data processing has attracted sustained attention as it can provide more
information for clustering. To integrate this information, one often utilizes the non-negative …
information for clustering. To integrate this information, one often utilizes the non-negative …
A novel approach to learning consensus and complementary information for multi-view data clustering
Effective methods are required to be developed that can deal with the multi-faceted nature of
the multi-view data. We design a factorization-based loss function-based method to …
the multi-view data. We design a factorization-based loss function-based method to …
Clustering multi-view data using non-negative matrix factorization and manifold learning for effective understanding: A survey paper
Multi-view data that contains the data represented in many types of features has received
much attention recently. The class of method utilizing non-negative matrix factorization …
much attention recently. The class of method utilizing non-negative matrix factorization …
Learning inter-and intra-manifolds for matrix factorization-based multi-aspect data clustering
Clustering on the data with multiple aspects, such as multi-view or multi-type relational data,
has become popular in recent years due to their wide applicability. The approach using …
has become popular in recent years due to their wide applicability. The approach using …
[HTML][HTML] Multi-view feature engineering for day-to-day joint clustering of multiple traffic datasets
A common task in traffic data analysis and management is categorizing different days based
on similarities in their network-wide traffic states. Given the multifaceted nature of traffic, it is …
on similarities in their network-wide traffic states. Given the multifaceted nature of traffic, it is …
A novel technique of using coupled matrix and greedy coordinate descent for multi-view data representation
The challenge of clustering multi-view data is to learn all latent features embedded in
multiple views accurately and efficiently. Existing Non-negative matrix factorization based …
multiple views accurately and efficiently. Existing Non-negative matrix factorization based …
Multi-type relational data clustering for community detection by exploiting content and structure information in social networks
Social Networks popularity has facilitated the providers with an opportunity to target specific
user groups for various applications such as viral marketing and customized programs …
user groups for various applications such as viral marketing and customized programs …
Deep Learning-Based Methods for Multi-aspect Data Clustering
Deep learning-based clustering approaches, which utilize deep neural networks to learn
latent feature representations for data clustering, have garnered significant attention in the …
latent feature representations for data clustering, have garnered significant attention in the …