MATA*: Combining Learnable Node Matching with A* Algorithm for Approximate Graph Edit Distance Computation
Author:
Affiliation:
1. Beihang University, Beijing, China
2. Huawei Noah's Ark Lab, Shenzhen, China
Funder
NSF of China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3583780.3614959
Reference42 articles.
1. Zeina Abu-Aisheh Romain Raveaux Jean-Yves Ramel and Patrick Martineau. 2015. An Exact Graph Edit Distance Algorithm for Solving Pattern Recognition Problems. In ICPRAM. 271--278. Zeina Abu-Aisheh Romain Raveaux Jean-Yves Ramel and Patrick Martineau. 2015. An Exact Graph Edit Distance Algorithm for Solving Pattern Recognition Problems. In ICPRAM. 271--278.
2. TaGSim
3. Yunsheng Bai Hao Ding Song Bian Ting Chen Yizhou Sun and Wei Wang. 2019. SimGNN: A Neural Network Approach to Fast Graph Similarity Computation. In WSDM. 384--392. Yunsheng Bai Hao Ding Song Bian Ting Chen Yizhou Sun and Wei Wang. 2019. SimGNN: A Neural Network Approach to Fast Graph Similarity Computation. In WSDM. 384--392.
4. Yunsheng Bai Hao Ding Ken Gu Yizhou Sun and Wei Wang. 2020. Learning-Based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching. In AAAI. 3219--3226. Yunsheng Bai Hao Ding Ken Gu Yizhou Sun and Wei Wang. 2020. Learning-Based Efficient Graph Similarity Computation via Multi-Scale Convolutional Set Matching. In AAAI. 3219--3226.
5. Comparing heuristics for graph edit distance computation
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