On graph query optimization in large networks
By Peixiang Zhao, Jiawei Han. Proceedings of the VLDB Endowment, 2010
418 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/478707d38e229d8ed8d0828e00d2feee9d15aea3
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In Artificial Intelligence
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Citations in the corpus
- Turboiso: towards ultrafast and robust subgraph isomorphism search in large graph databases (2013, methodology): “Subgraph isomorphism search is actively used in many applications such as protein interaction analysis [21], graph classification [4], computer-aided design of electronic circuits [10], scene analysis [1], and chemical compound search [17].”
- An In-depth Comparison of Subgraph Isomorphism Algorithms in Graph Databases (2012, methodology): “In [5,18], k is set to 1000.”
- Efficient Subgraph Matching by Postponing Cartesian Products (2016, methodology): “We evaluate the algorithms on three real graphs, HPRD 1 , Yeast, and Human, which are widely used in existing works [8, 12, 14, 22].”
- Efficient Subgraph Matching on Billion Node Graphs (2012, methodology): “The indices in [33] and [34] use a signature representing neighborhoods within a given distance for each vertex.”