Frequent Pattern-based Graph Exploration
Author:
Affiliation:
1. School of Computer Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang, China
2. Microsoft Research Asia, Beijing, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3356422.3356446
Reference33 articles.
1. James Abello Fred Hohman Varun Bezzam and Duen Horng Chau. 2018. Large Graph Exploration via Subgraph Discovery and Decomposition. arXiv:1808.04414 [cs] (Aug. 2018). http://arxiv.org/abs/1808.04414 arXiv: 1808.04414. James Abello Fred Hohman Varun Bezzam and Duen Horng Chau. 2018. Large Graph Exploration via Subgraph Discovery and Decomposition. arXiv:1808.04414 [cs] (Aug. 2018). http://arxiv.org/abs/1808.04414 arXiv: 1808.04414.
2. Nesreen K Ahmed Ryan Rossi John Boaz Lee Theodore L Willke Rong Zhou Xi-angnan Kong and Hoda Eldardiry. 2018. Learning role-based graph embeddings. arXiv preprint arXiv:1802.02896 (2018). Nesreen K Ahmed Ryan Rossi John Boaz Lee Theodore L Willke Rong Zhou Xi-angnan Kong and Hoda Eldardiry. 2018. Learning role-based graph embeddings. arXiv preprint arXiv:1802.02896 (2018).
3. Subgraph isomorphism, matching relational structures and maximal cliques
4. George Berry. 2018. Role action embeddings: scalable representation of network positions. arXiv preprint arXiv:1811.08019 (2018). George Berry. 2018. Role action embeddings: scalable representation of network positions. arXiv preprint arXiv:1811.08019 (2018).
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