Counting frequent patterns in large labeled graphs: a hypergraph-based approach

DOI10.1007/s10618-020-00686-9zbMath1477.68092OpenAlexW3022749277MaRDI QIDQ2194034

Yi-Cheng Tu, Jinghan Meng, Napath Pitaksirianan

Publication date: 25 August 2020

Published in: Data Mining and Knowledge Discovery (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10618-020-00686-9

zbMATH Keywords

hypergraphdata mininggraph miningsupport measure

Mathematics Subject Classification ID

Applications of mathematical programming (90C90) Database theory (68P15) Hypergraphs (05C65) Graph theory (including graph drawing) in computer science (68R10) Approximation algorithms (68W25)

Uses Software

• nauty
• CPLEX
• Traces
• gSpan
• GitHub
• CloseGraph

Cites Work

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• Practical graph isomorphism. II.
• Support measures for graph data
• On the Size of Systems of Sets Every t of which Have an SDR, with an Application to the Worst-Case Ratio of Heuristics for Packing Problems
• Smoothed analysis of algorithms
• On the Shannon capacity of a graph
• Reducibility among Combinatorial Problems

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