Top- k frequent induced subgraph mining using sampling
Author:
Affiliation:
1. Kyung Hee University, Republic of Korea
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3007818.3007839
Reference11 articles.
1. Frequent pattern mining: current status and future directions
2. The Gaston Tool for Frequent Subgraph Mining
3. Influence and correlation in social networks
Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. FS3change: A Scalable Method for Change Pattern Mining;IEEE Transactions on Software Engineering;2023
2. A survey of pattern mining in dynamic graphs;WIREs Data Mining and Knowledge Discovery;2020-05-20
3. TKG: Efficient Mining of Top-K Frequent Subgraphs;Big Data Analytics;2019
4. Data and Visual Analytics for Emerging Databases;Lecture Notes in Electrical Engineering;2017-10-14
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