Knowledge graphs: Opportunities and challenges

C Peng, F **a, M Naseriparsa, F Osborne - Artificial Intelligence Review, 2023‏ - Springer
With the explosive growth of artificial intelligence (AI) and big data, it has become vitally
important to organize and represent the enormous volume of knowledge appropriately. As …

A review of graph neural networks: concepts, architectures, techniques, challenges, datasets, applications, and future directions

B Khemani, S Patil, K Kotecha, S Tanwar - Journal of Big Data, 2024‏ - Springer
Deep learning has seen significant growth recently and is now applied to a wide range of
conventional use cases, including graphs. Graph data provides relational information …

Combating misinformation in the age of llms: Opportunities and challenges

C Chen, K Shu - AI Magazine, 2024‏ - Wiley Online Library
Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …

Rethinking graph neural networks for anomaly detection

J Tang, J Li, Z Gao, J Li - International conference on …, 2022‏ - proceedings.mlr.press
Abstract Graph Neural Networks (GNNs) are widely applied for graph anomaly detection. As
one of the key components for GNN design is to select a tailored spectral filter, we take the …

Combating misinformation in the era of generative AI models

D Xu, S Fan, M Kankanhalli - Proceedings of the 31st ACM International …, 2023‏ - dl.acm.org
Misinformation has been a persistent and harmful phenomenon affecting our society in
various ways, including individuals' physical health and economic stability. With the rise of …

Addressing heterophily in graph anomaly detection: A perspective of graph spectrum

Y Gao, X Wang, X He, Z Liu, H Feng… - Proceedings of the ACM …, 2023‏ - dl.acm.org
Graph anomaly detection (GAD) suffers from heterophily—abnormal nodes are sparse so
that they are connected to vast normal nodes. The current solutions upon Graph Neural …

Domain-specific knowledge graphs: A survey

B Abu-Salih - Journal of Network and Computer Applications, 2021‏ - Elsevier
Abstract Knowledge Graphs (KGs) have made a qualitative leap and effected a real
revolution in knowledge representation. This is leveraged by the underlying structure of the …

Fairness in graph mining: A survey

Y Dong, J Ma, S Wang, C Chen… - IEEE Transactions on …, 2023‏ - ieeexplore.ieee.org
Graph mining algorithms have been playing a significant role in myriad fields over the years.
However, despite their promising performance on various graph analytical tasks, most of …

An attentive survey of attention models

S Chaudhari, V Mithal, G Polatkan… - ACM Transactions on …, 2021‏ - dl.acm.org
Attention Model has now become an important concept in neural networks that has been
researched within diverse application domains. This survey provides a structured and …

Twibot-22: Towards graph-based twitter bot detection

S Feng, Z Tan, H Wan, N Wang… - Advances in …, 2022‏ - proceedings.neurips.cc
Twitter bot detection has become an increasingly important task to combat misinformation,
facilitate social media moderation, and preserve the integrity of the online discourse. State-of …