HONEM learns embeddings for higher-order networks capturing non-Markovian dependencies and outperforms baselines on node classification, reconstruction, link prediction, and visualization.
node2vec: Scalable feature learning for networks
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2019 2verdicts
UNVERDICTED 2representative citing papers
Framework applies signed graphs and group partitioning to CBDB dataset to extract ancient figures' power and camps, with case study results matching historical facts.
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HONEM: Learning Embedding for Higher Order Networks
HONEM learns embeddings for higher-order networks capturing non-Markovian dependencies and outperforms baselines on node classification, reconstruction, link prediction, and visualization.
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Computing Lens for Exploring the Historical People's Social Network
Framework applies signed graphs and group partitioning to CBDB dataset to extract ancient figures' power and camps, with case study results matching historical facts.