Results 51 to 60 of about 146,643 (141)

Enhanced MCL Clustering

مجلة علوم ذي قار, 2019
  The goal of graph clustering is to partition vertices in a large graph into different clusters based on various criteria such as vertex connectivity or neighborhood similarity.
Mouiad Abid Hani
doaj   +4 more sources

Dual Smooth Graph Convolutional Clustering for Large-Scale Hyperspectral Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Large-scale hyperspectral image (HSI) clustering remains a fundamental and challenging task due to tremendous spatial scales, abundant spectral band information, and lack of prior information.
Jiaxin Chen, Shujun Liu, Huajun Wang
doaj   +1 more source

Cloud Service Community Detection for Real-World Service Networks Based on Parallel Graph Computing

IEEE Access, 2019
Heterogeneous information networks (e.g. cloud service relation networks and social networks), where multiple-typed objects are interconnected, can be structured by big graphs. A major challenge for clustering in such big graphs is the complex structures
Yu Lei, Philip S. Yu
doaj   +1 more source

A Unified Graph Theory Approach: Clustering and Learning in Criminal Data

Mathematics
Crime report clustering plays a critical role in modern law enforcement, enabling the identification of patterns and trends essential for proactive policing.
Haifa Al-Ibrahim, Heba Kurdi
doaj   +1 more source

Capped $l_1$ -Norm Sparse Representation Method for Graph Clustering

IEEE Access, 2019
As one of the most popular clustering techniques, graph clustering has attracted many researchers in the field of machine learning and data mining. Generally speaking, graph clustering partitions the data points into different categories according to ...
Mulin Chen, Qi Wang, Shangdong Chen, Xuelong Li   +3 more
doaj   +1 more source

Automatic classification of protein structures relying on similarities between alignments

BMC Bioinformatics, 2012
Background Identification of protein structural cores requires isolation of sets of proteins all sharing a same subset of structural motifs. In the context of an ever growing number of available 3D protein structures, standard and automatic clustering ...
Santini Guillaume, Soldano Henry, Pothier Joël   +2 more
doaj   +1 more source

Variational Graph Generator for Multiview Graph Clustering

IEEE Transactions on Neural Networks and Learning Systems
Multi-view graph clustering (MGC) methods are increasingly being studied due to the explosion of multi-view data with graph structural information. The critical point of MGC is to better utilize view-specific and view-common information in features and graphs of multiple views. However, existing works have an inherent limitation that they are unable to
Jianpeng Chen, Yawen Ling, Jie Xu, Yazhou Ren, Shudong Huang, Xiaorong Pu, Zhifeng Hao, Philip S. Yu, Lifang He   +8 more
openaire   +3 more sources

Multi-view dual anchor graph fuzzy clustering

Nantong Daxue xuebao. Ziran kexue ban
In recent years, with the rapid development of multi-view learning, how to effectively integrate information from different views for clustering analysis has become an important research topic in both academia and industry,driving the emergence of ...
ZHU Chenghao；DING Weiping；ZHANG Wei
doaj   +1 more source

ADPSCAN: Structural Graph Clustering with Adaptive Density Peak Selection and Noise Re-Clustering

Applied Sciences
Structural graph clustering is a data analysis technique that groups nodes within a graph based on their connectivity and structural similarity. The Structural graph clustering SCAN algorithm, a density-based clustering method, effectively identifies ...
Xinyu Du, Fangfang Li, Xiaohua Li, Ge Yu
doaj   +1 more source

Graph Clustering with High-Order Contrastive Learning. [PDF]

Entropy (Basel), 2023
Li W, Zhu E, Wang S, Guo X.
europepmc   +1 more source