Graph representation learning and its applications: a survey
Graphs are data structures that effectively represent relational data in the real world. Graph
representation learning is a significant task since it could facilitate various downstream …
representation learning is a significant task since it could facilitate various downstream …
Data augmentation for graph classification
Graph classification, which aims to identify the category labels of graphs, plays a significant
role in drug classification, toxicity detection, protein analysis etc. However, the limitation of …
role in drug classification, toxicity detection, protein analysis etc. However, the limitation of …
M-evolve: structural-mapping-based data augmentation for graph classification
Graph classification, which aims to identify the category labels of graphs, plays a significant
role in drug classification, toxicity detection, protein analysis etc. However, the limitation of …
role in drug classification, toxicity detection, protein analysis etc. However, the limitation of …
Understanding the characteristics of COVID-19 misinformation communities through graphlet analysis
Online social networks serve as a convenient way to connect, share, and promote content
with others. As a result, these networks can be used with malicious intent, causing disruption …
with others. As a result, these networks can be used with malicious intent, causing disruption …
A Novel Prompt Tuning for Graph Transformers: Tailoring Prompts to Graph Topologies
J Wang, Z Deng, T Lin, W Li, S Ling - Proceedings of the 30th ACM …, 2024 - dl.acm.org
Deep graph prompt tuning (DeepGPT), which only tunes a set of continuous prompts for
graph transformers, significantly decreases the storage usage during training. However …
graph transformers, significantly decreases the storage usage during training. However …
Compressing and mining social network data
CCJ Hryhoruk, CK Leung - Proceedings of the 2021 IEEE/ACM …, 2021 - dl.acm.org
Nowadays, social networking is popular. As such, numerous social networking sites (eg,
Facebook, YouTube, Instagram) are generating very large volumes of social data rapidly …
Facebook, YouTube, Instagram) are generating very large volumes of social data rapidly …
A graph entropy measure from urelement to higher-order graphlets for network analysis
Graph entropy measures have recently gained wide attention for identifying and
discriminating various networks in biology, society, transportation, etc. However, existing …
discriminating various networks in biology, society, transportation, etc. However, existing …
Beyond graph neural networks with lifted relational neural networks
We introduce a declarative differentiable programming framework, based on the language of
Lifted Relational Neural Networks, where small parameterized logic programs are used to …
Lifted Relational Neural Networks, where small parameterized logic programs are used to …
A theoretical approach for discovery of friends from directed social graphs
Since social networking has been popular in the current era of big data, numerous social
networking sites (eg, Instagram, Twitter) have generated huge volumes of social data at a …
networking sites (eg, Instagram, Twitter) have generated huge volumes of social data at a …
A mathematical model for friend discovery from dynamic social graphs
Nowadays, social networking is popular. As such, numerous social networking sites (eg,
Facebook, YouTube, Instagram) are generating very large volumes of social data rapidly …
Facebook, YouTube, Instagram) are generating very large volumes of social data rapidly …