Repository logo

Infoscience

  • English
  • French
Log In
Logo EPFL, École polytechnique fédérale de Lausanne

Infoscience

  • English
  • French
Log In
  1. Home
  2. Academic and Research Output
  3. Journal articles
  4. MARGIN: Maximal frequent subgraph mining
 
research article

MARGIN: Maximal frequent subgraph mining

Valluri, Ramachandra Satyanarayana  
•
Thomas, Lini T.
•
Karlapalem, Kamalakar
2010
ACM Transactions on Knowledge Discovery from Data

The exponential number of possible subgraphs makes the problem of frequent subgraph mining a challenge. The set of maximal frequent subgraphs is much smaller to that of the set of frequent subgraphs providing ample scope for pruning. MARGIN is a maximal subgraph mining algorithm that moves among promising nodes of the search space along the “border” of the infrequent and frequent subgraphs. This drastically reduces the number of candidate patterns in the search space. The proof of correctness of the algorithm is presented. Experimental results validate the efficiency and utility of the technique proposed.

  • Details
  • Metrics
Type
research article
DOI
10.1145/1839490.1839491
Author(s)
Valluri, Ramachandra Satyanarayana  
Thomas, Lini T.
Karlapalem, Kamalakar
Date Issued

2010

Published in
ACM Transactions on Knowledge Discovery from Data
Volume

4

Issue

3

Start page

10

Editorial or Peer reviewed

NON-REVIEWED

Written at

EPFL

EPFL units
IIF  
Available on Infoscience
August 24, 2015
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/117308
Logo EPFL, École polytechnique fédérale de Lausanne
  • Contact
  • infoscience@epfl.ch

  • Follow us on Facebook
  • Follow us on Instagram
  • Follow us on LinkedIn
  • Follow us on X
  • Follow us on Youtube
AccessibilityLegal noticePrivacy policyCookie settingsEnd User AgreementGet helpFeedback

Infoscience is a service managed and provided by the Library and IT Services of EPFL. © EPFL, tous droits réservés