By Topic

MOEP-SO: A multiobjective evolutionary programming algorithm for graph mining

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Shelokar, P. ; Eur. Centre for Soft Comput., Mieres, Spain ; Quirin, A. ; Cordon, O.

Subgraph Mining aims to find frequent, descriptive and interesting subgraphs in a graph database. Usually, this search involves simple user-defined thresholds and is only driven by a single-objective. In this paper, we propose an Evolutionary Multiobjective Optimization algorithm, called MOEP-SO, to mine subgraphs from graph-represented data by maximizing two objectives, support and size of the subgraphs. Experimental results on synthetic and real-life graph-based datasets validate the utility of the proposed methodology when benchmarked against classical single-objective methods and their previous, non-evolutionary multiobjective extensions.

Published in:

Intelligent Systems Design and Applications (ISDA), 2011 11th International Conference on

Date of Conference:

22-24 Nov. 2011