.png){kind=icon}
返回
Vicinal Vertex Allocation for Matrix Factorization in Networks
.png){kind=icon}
OA
AI
DOI：10.1109/TCYB.2021.3051606.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this article, we present a novel matrix-factorization-based model, labeled here as Vicinal vertex allocated matrix factorization (VVAMo), for uncovering clusters in network data. Different from the past related efforts of network clustering, which consider the edge structure, vertex features, or both in their design, the proposed model includes the additional detail on vertex inclinations with respect to topology and features into the learning. In particular, by taking the latent preferences between vicinal vertices into consideration, VVAMo is then able to uncover network clusters composed of proximal vertices that share analogous inclinations, and correspondingly high structural and feature correlations. To ensure such clusters are effectively uncovered, we propose a unified likelihood function for VVAMo and derive an alternating algorithm for optimizing the proposed function. Subsequently, we provide the theoretical analysis of VVAMo, including the convergence proof and computational complexity analysis. To investigate the effectiveness of the proposed model, a comprehensive empirical study of VVAMo is conducted using extensive commonly used realistic network datasets. The results obtained show that VVAMo attained superior performances over existing classical and state-of-the-art approaches.
Keyword:
Computational modeling
Correlation
Data models
Task analysis
Probabilistic logic
Network topology
Adaptation models
Community detection
complex network
graph clustering
network clustering
probabilistic matrix factorization
vicinal vertex-allocated matrix factorization (VVAMo)
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
10.5
论文数:
1.1W
被引数:
5.0W
机构
引用论文
BioGRID: a general repository for interaction datasetsBioGRID: 交互数据集的通用存储库.png)
NUCLEIC ACIDS RESEARCHOAAI
NUCLEIC ACIDS RESEARCHIF13.1
OAAI分享收藏A Multiobjective Evolutionary Algorithm Based on Structural and Attribute Similarities for Community Detection in Attributed Networks基于结构和属性相似性的多目标进化算法在属性网络社区发现中的应用
PREAI
分享收藏Tinnitus Retraining Therapy (TRT) as a Method for Treatment of Tinnitus and Hyperacusis Patients耳鸣再训练疗法 (TRT) 作为治疗耳鸣和高亢患者的方法
PREAI
分享收藏
查看更多内容