Efficiently mining \(\delta \)-tolerance closed frequent subgraphs

DOI10.1007/s10994-010-5215-6zbMath1237.68168OpenAlexW2161646342WikidataQ62669631 ScholiaQ62669631MaRDI QIDQ413834

Hiroshi Mamitsuka, Ichigaku Takigawa

Publication date: 8 May 2012

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10994-010-5215-6

zbMATH Keywords

frequent subgraph mining\(\delta \)-tolerance closednesspartial reverse search

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Graph theory (including graph drawing) in computer science (68R10)

Related Items

Summarization and visualization of multi-level and multi-dimensional itemsets ⋮ Mining approximate patterns with frequent locally optimal occurrences

Uses Software

• gSpan
• ParMol
• Fg-index
• CloseGraph

Cites Work

• Unnamed Item
• Reverse search for enumeration
• Full Perfect Extension Pruning for Frequent Subgraph Mining
• Depth-First Search and Linear Graph Algorithms