# DeepMultiviewClustering

**Repository Path**: jshncu/DeepMultiviewClustering

## Basic Information

- **Project Name**: DeepMultiviewClustering
- **Description**: Code for Deep Multiview Clustering
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2026-03-30
- **Last Updated**: 2026-03-30

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# DeepMultiviewClustering

#### Introduction
This package includes the proposed multi-view data clustering methods. The code shared in this repository implements the algorithms for the models proposed in the following papers. Welcome to use our models as the comparison methods in your papers. If you have any questions, you are welcome to send an email to me (jianshengwu@ncu.edu.cn). The source code for most of our published works is publicly available on Gitee. Should you be unable to locate the code for a specific work there, you can alternatively search for it on our Github repository (https://github.com/jshncu) or contact us via email for assistance.

#### 软件架构
1、Method 1: DCMGAL 
  Run the python script "main.m" in the folder "DCMGAL" to get the clustering result.

 **_DCMGAL (Dual Contrastive Learning with Graph Masking: A Self-Supervised Framework for Multi-View Clustering: https://doi.org/10.1016/j.neunet.2026.108894 )_** 

@article{DLMVC_DCMGAL_Wu_2026, title={Dual Contrastive Learning with Graph Masking: A Self-Supervised Framework for Multi-View Clustering}, author={Wu, Jian-Sheng and Wen-Ting, Li and Wu, Jun-Yun and Min, Weidong}, journal={Neural Networks}, volume={***}, pages={108894}, year={2026}, publisher={Elsevier}, doi={https://doi.org/10.1016/j.neunet.2026.108894}, }