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Euler: Detecting Network Lateral Movement via Scalable Temporal Link Prediction
ACM Transactions on Privacy and Security, 2023Lateral movement is a key stage of system compromise used by advanced persistent threats. Detecting it is no simple task. When network host logs are abstracted into discrete temporal graphs, the problem can be reframed as anomalous edge detection in an ...
I. J. King, Huimin Huang
semanticscholar +1 more source
Community-enhanced Link Prediction in Dynamic Networks
ACM Transactions on the Web, 2023The growing popularity of online social networks is quite evident nowadays and provides an opportunity to allow researchers in finding solutions for various practical applications.
Mukesh Kumar +3 more
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Heterogeneous Hypergraph Variational Autoencoder for Link Prediction
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021Link prediction aims at inferring missing links or predicting future ones based on the currently observed network. This topic is important for many applications such as social media, bioinformatics and recommendation systems.
Haoyi Fan +6 more
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Few-shot Link Prediction in Dynamic Networks
Web Search and Data Mining, 2022Dynamic link prediction, which aims at forecasting future edges of a node in a dynamic network, is an important problem in network science and has a wide range of real-world applications.
Cheng Yang +6 more
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Generative dynamic link prediction
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2019In networks, a link prediction task aims at learning potential relations between nodes to predict unknown potential linkage states. At present, most link prediction methods are used to process static networks. These methods cannot produce good prediction results for dynamic networks.
Jinyin Chen +6 more
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Knowledge Graph Large Language Model (KG-LLM) for Link Prediction
Asian Conference on Machine LearningThe task of multi-hop link prediction within knowledge graphs (KGs) stands as a challenge in the field of knowledge graph analysis, as it requires the model to reason through and understand all intermediate connections before making a prediction. In this
Dong Shu +6 more
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Link direction for link prediction
Physica A: Statistical Mechanics and its Applications, 2017Abstract Almost all previous studies on link prediction have focused on using the properties of the network to predict the existence of links between pairs of nodes. Unfortunately, previous methods rarely consider the role of link direction for link prediction.
Ke-ke Shang +2 more
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Impact of Centrality Measures on the Common Neighbors in Link Prediction for Multiplex Networks
Big Data, 2022Complex networks are representations of real-world systems that can be better modeled as multiplex networks, where the same nodes develop multi-type connections.
E. Nasiri +3 more
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Predicting the Link Strength of "Newborn" Links
Proceedings of the 25th International Conference Companion on World Wide Web - WWW '16 Companion, 2016Measurements of online social networks (OSNs) support the common fact that not all links carry the same social value, and that the strength of each link is strictly related to the frequency of interactions between the connected users. In this paper, we investigate the predictability of the interactions on OSN links by wondering if it is possible to ...
M. Zignani, S. Gaito, G.P. Rossi
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2019 IEEE International Conference on Big Data (Big Data), 2019
Due to its universal applications in the domain of social network analysis, e-commerce, and recommendation systems, the task of link prediction has received enormous attention from the data mining and machine learning communities over the last decade.
Andrew Stanhope +4 more
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Due to its universal applications in the domain of social network analysis, e-commerce, and recommendation systems, the task of link prediction has received enormous attention from the data mining and machine learning communities over the last decade.
Andrew Stanhope +4 more
openaire +1 more source