This repository lists related work using MVC methods for applications. We hope to investigate the special issues in application scenarios of multi-view clustering analysis, to achieve the future improvements on MVC algorithms for this community, so feel free to contact me in this repository for updating (recommended paper, datasource, code...).
DEMOC: a deep embedded multi-omics learning approach for clustering single-cell CITE-seq data, Zou et al.
scBridge embraces cell heterogeneity in single-cell RNA-seq and ATAC-seq data integration, Li et al.
Biotypes of major depressive disorder identified by a multiview clustering framework, Chen et al.
Multi-omics clustering based on dual contrastive learning for cancer subtype identification, Chen et al.
Recursive integration of synergised graph representations of multi-omics data for cancer subtypes identification, Madhumita et al.
A multiobjective multi-view cluster ensemble technique: Application in patient subclassification, Mitra et al.
Multi-omic and multi-view clustering algorithms: review and cancer benchmark, Rappoport et al.
Consensus clustering applied to multi-omics disease subtyping, Brière et al.
A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data, Mo et al.
Integrate multi-omic data using affinity network fusion (ANF) for cancer patient clustering, Ma et al.
Multi-View Clustering of Clinical Documents Based on Conditions and Medical Responses of Patients, Sabthami et al.
CMC: A consensus multi-view clustering model for predicting Alzheimer's disease progression, Zhang et al.
Protein complex detection based on partially shared multi-view clustering, Ou-Yang et al.
Multi-View Spectral Clustering Based on Multi-Smooth Representation Fusion for Cancer Subtype Prediction, Liu et al.
Multi-view spectral clustering with latent representation learning for applications on multi-omics cancer subtyping, Ge et al.
MLysPRED: graph-based multi-view clustering and multi-dimensional normal distribution resampling techniques to predict multiple lysine sites, Zuo et al.
Research on children's respiratory diseases based on partition level multi-view clustering, Zhang et al.
Multi-graph Clustering Based on Interior-Node Topology with Applications to Brain Networks, Ma et al.
Clustering of single-cell multi-omics data with a multimodal deep learning method, Lin et al.
Task-optimized User Clustering based on Mobile App Usage for Cold-start Recommendations, Liu et al.
Comment-based Multi-View Clustering of Web 2.0 Items, He et al.
Social web video clustering based on multi-view clustering via nonnegative matrix factorization, Mekthanavanh et al.
Web Items Recommendation Based on Multi-View Clustering, Yu et al.
Multi-View Clustering of Web Documents using Multi-Objective Genetic Algorithm, Wahid et al.
Multi-view clustering for mining heterogeneous social network data, Greene et al.
A robust multi-view clustering method for community detection combining link and content information, He et al.
Multi-view multi-objective clustering-based framework for scientific document summarization using citation context, Saini et al.
Multimodal Clustering for Community Detection, Ignatov et al.
Graph-Based Multimodal Clustering for Social Event Detection in Large Collections of Images, Petkos et al.
Social event detection using multimodal clustering and integrating supervisory signals, Petkos et al.
Multi-View Clustering-Based Time Series Empirical Tropospheric Delay Correction, Gao et al.
An Equivalent Model of Wind Farm Based on Multivariate Multi-Scale Entropy and Multi-View Clustering, Han et al.
An Analysis of Current Trends in CBR Research Using Multiview Clustering, Greene et al.
Multigraph Spectral Clustering for Joint Content Delivery and Scheduling in Beam-Free Satellite Communications, Vázquez et al.
Deep Multimodal Clustering for Unsupervised Audiovisual Learning, Hu et al.
Multi-view clustering based on graph-regularized nonnegative matrix factorization for object recognition, Zhang et al.
MMatch: Semi-Supervised Discriminative Representation Learning for Multi-View Classification, Wang et al.
Attributed multiplex graph clustering: A heuristic clustering-aware network embedding approach, Han et al.
To be updated...