[HTML][HTML] Locality-aware subgraphs for inductive link prediction in knowledge graphs
Recent methods for inductive reasoning on Knowledge Graphs (KGs) transform the link
prediction problem into a graph classification task. They first extract a subgraph around each …
prediction problem into a graph classification task. They first extract a subgraph around each …
Overlap** community detection by constrained personalized PageRank
Y Gao, X Yu, H Zhang - Expert Systems with Applications, 2021 - Elsevier
Given a network, local community detection (aka graph clustering) methods aim at finding
communities around the selected initial nodes (also referred to as seeds, starting nodes or …
communities around the selected initial nodes (also referred to as seeds, starting nodes or …
Local community detection in multiple networks
Local community detection aims to find a set of densely-connected nodes containing given
query nodes. Most existing local community detection methods are designed for a single …
query nodes. Most existing local community detection methods are designed for a single …
Cengcn: Centralized convolutional networks with vertex imbalance for scale-free graphs
Graph Convolutional Networks (GCNs) have achieved impressive performance in a wide
variety of areas, attracting considerable attention. The core step of GCNs is the information …
variety of areas, attracting considerable attention. The core step of GCNs is the information …
Adaptive target community search with sample expansion
Target community search aims to search cohesive communities consistent with the user's
preference revealed by query nodes, which is a query-dependent variant of community …
preference revealed by query nodes, which is a query-dependent variant of community …
Attributed multi-query community search via random walk similarity
Community search aims to provide efficient solutions for searching high-quality communities
via given sample nodes from network. Much research effort has devoted to mining a single …
via given sample nodes from network. Much research effort has devoted to mining a single …
Identifying vital nodes for influence maximization in attributed networks
Y Wang, Y Zheng, Y Liu - Scientific Reports, 2022 - nature.com
Identifying a set of vital nodes to achieve influence maximization is a topic of general interest
in network science. Many algorithms have been proposed to solve the influence …
in network science. Many algorithms have been proposed to solve the influence …
Look before you leap: Confirming edge signs in random walk with restart for personalized node ranking in signed networks
In this paper, we address the personalized node ranking (PNR) problem for signed
networks, which aims to rank nodes in an order most relevant to a given seed node in a …
networks, which aims to rank nodes in an order most relevant to a given seed node in a …
Span-core decomposition for temporal networks: Algorithms and applications
When analyzing temporal networks, a fundamental task is the identification of dense
structures (ie, groups of vertices that exhibit a large number of links), together with their …
structures (ie, groups of vertices that exhibit a large number of links), together with their …
Graph clustering using triangle-aware measures in large networks
Y Gao, X Yu, H Zhang - Information Sciences, 2022 - Elsevier
Graph clustering (also referred to as community detection) is an important topic in network
analysis. Although a large amount of literature has been published on the problem, most of …
analysis. Although a large amount of literature has been published on the problem, most of …