Fang U, Li M, Li J, et al. A Comprehensive Survey on Multi-view Clustering[J]. IEEE Transactions on Knowledge and Data Engineering, 2023.论文链接 论文导读 对Multi-view clustering (MVC)做文献综述,主要包括两种方法: heuristic-based multi-view clustering (HMVC) nonnegative matrix factorisation g...
Multi-view graph clustering is an attentional research topic in recent years due to its wide applications. According to recent surveys, most existing works focus on incorporating comprehensive information among multiple views to achieve the clustering task. However, these studies pay less attention to ...
Multi-view clustering (MVC) algorithms usually have good performance which benefits from the merit that multi-view data contains more comprehensive informa... J He,H Chen,TWJ Li - Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving ...
Graphs are usually built to outline the correlation between multi-model objects in clustering task, and multi-view graph clustering aims to learn a consensus graph that integrates the spatial property of each view. Nevertheless, most graph-based models merely consider the overall structure from all ...
We call this graph matrix the similarity-induced graph (SIG) matrix. Although such methods have achieved state-of-the-art performances, most are not comprehensive. First, there is not a general graph-based system for multi-view clustering. We propose a general approach in this paper. Second,...
but also contains a lot of knowledge to mine and apply. Some of the single-view data clustering techniques have been improved to analyze multi-view data by extending the structure of the objective function or building associative models. Currently, multi-view clustering methods are quite rich and...
The average of silhouette width of all spots as the final metrics (ASW) to evaluate clustering performance. Identification of SVGs We constructed KNN graph for each spot based on the learned low-dimensional representations (\(R\)), and adopted the KNN-smoothing algorithm to aggregate information...
3). For PDBbind_2016 and PDBbind_2019, we constructed a drug graph using the atoms from the provided structure files (.mol2 or.sdf) as vertices, and the bonds between these atoms as edges. Simultaneously, to capture more comprehensive features of drugs, we built the line graphs based on...
In recent years, incomplete multi-view clustering has attracted much attention and achieved promising performances through the use of deep learning. However, only a few prior methods are concerned with joint missing data recovery and clustering. In this paper, we present a graph t-SNE multi-view...
Comprehensive experiments on six benchmark datasets validate the effectiveness and superiority of the proposed MSCNLG. Introduction Clustering is an important task in unsupervised learning, which can be a prepossessing step to assist other learning tasks or a stand-alone exploratory tool to uncover ...