Unsupervised learning for community detection in attributed networks based on graph convolutional network
X Wang, J Li, L Yang, H Mi - Neurocomputing, 2021 - Elsevier
Community detection has emerged during the last decade as one of the most challenging
problems in network science, which has been revisited with network representation learning …
problems in network science, which has been revisited with network representation learning …
An evolutionary multiobjective optimization based fuzzy method for overlapping community detection
In the last decade, the detection of overlapping communities has received increasing
attention in network science. Among various clustering techniques, the fuzzy clustering has …
attention in network science. Among various clustering techniques, the fuzzy clustering has …
Community-based seeds selection algorithm for location aware influence maximization
In this paper, we study the location aware influence maximization problem, which finds a
seed set to maximize the influence spread on targeted users for a given query. In particular …
seed set to maximize the influence spread on targeted users for a given query. In particular …
Evolutionary multiobjective overlapping community detection based on similarity matrix and node correction
The method of overlapping community detection based on fuzzy clustering is sensitive to the
initialization of community centers, which easily traps in local optima and leads to node …
initialization of community centers, which easily traps in local optima and leads to node …
A distributed overlapping community detection model for large graphs using autoencoder
Community detection has become pervasive in finding similar patterns present in the
network. It aims to discover lower dimensional embedding for representing the structure of …
network. It aims to discover lower dimensional embedding for representing the structure of …
[PDF][PDF] An Entity-Association-Based Matrix Factorization Recommendation Algorithm.
G Liu, K Meng, J Ding, JP Nees, H Guo… - … , Materials & Continua, 2019 - cdn.techscience.cn
Collaborative filtering is the most popular approach when building recommender systems,
but the large scale and sparse data of the user-item matrix seriously affect the …
but the large scale and sparse data of the user-item matrix seriously affect the …
Overlapping community detection in networks based on Neutrosophic theory
M Gholami, A Sheikhahmadi, K Khamforoosh… - Physica A: Statistical …, 2022 - Elsevier
Discovering community structure is one of the most intensively studied problems in network
science. Many real networks are composed of nodes belonging to multiple communities. In …
science. Many real networks are composed of nodes belonging to multiple communities. In …
Weakly-supervised learning for community detection based on graph convolution in attributed networks
X Wang, J Li, L Yang, H Mi, JY Yu - International Journal of Machine …, 2021 - Springer
Community detection in complex networks has been revisited with graph deep learning
recently and has attracted great attention. It is often challenging to uncover underlying …
recently and has attracted great attention. It is often challenging to uncover underlying …
[PDF][PDF] 基于贡献函数的重叠社区划分算法
刘功申， 孟魁， 郭弘毅， 苏波， 李建华 - 电子与信息学报, 2017 - edit.jeit.ac.cn
现实世界中的网络结构呈现出重叠社区的特征. 在研究经典的标签算法的基础上,
该文提出基于贡献函数的重叠社区发现算法. 算法将每个节点用三元组(阈值, 标签, 从属系数) …
该文提出基于贡献函数的重叠社区发现算法. 算法将每个节点用三元组(阈值, 标签, 从属系数) …
基于节点社会性的无线网络编码传输策略研究.
张晓军， 李领治， 朱艳琴 - Application Research of …, 2019 - search.ebscohost.com
延迟容忍网络是一种缺乏持续连接的新型网络体系结构, 选择合适的转发节点是实现延迟容忍
网络高效的转发和投递消息的关键问题. 由于节点移动性和网络拓扑动态变化等会对延迟容忍 …
网络高效的转发和投递消息的关键问题. 由于节点移动性和网络拓扑动态变化等会对延迟容忍 …