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Article
A hidden challenge of link prediction: which pairs to check?
The traditional setup of link prediction in networks assumes that a test set of node pairs, which is usually balanced, is available over which to predict the presence of links. However, in practice, there is n...
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Article
Fast network discovery on sequence data via time-aware hashing
Discovering and analyzing networks from non-network data is a task with applications in fields as diverse as neuroscience, genomics, climate science, economics, and more. In domains where networks are discover...
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Article
On effective and efficient graph edge labeling
Graphs, such as social, road and information networks, are ubiquitous as they naturally model entities and their relationships. Many query processing tasks on graphs are concerned about efficiently accessing n...
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Chapter and Conference Paper
HashAlign: Hash-Based Alignment of Multiple Graphs
Fusing or aligning two or more networks is a fundamental building block of many graph mining tasks (e.g., recommendation systems, link prediction, collective analysis of networks). Most past work has focused o...
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Article
Discovery of “comet” communities in temporal and labeled graphs Com \(^2\)
While the analysis of unlabeled networks has been studied extensively in the past, finding patterns in different kinds of labeled graphs is still an open challenge. Given a large edge-labeled network, e.g., a ...