Three-objective subgraph mining using multiobjective evolutionary programming

作者：

Highlights：

• Formulation of a three-objective graph-based data mining (GBDM) problem.

• Multiobjective evolutionary programming for GBDM.

• Diversified solution selection through summation of objectives method.

• Pareto-based dominance criteria.

• Use of crowding distance method to maintain external archive.

摘要

•Formulation of a three-objective graph-based data mining (GBDM) problem.•Multiobjective evolutionary programming for GBDM.•Diversified solution selection through summation of objectives method.•Pareto-based dominance criteria.•Use of crowding distance method to maintain external archive.

论文关键词：Graph-based data mining,Frequent subgraph mining,Multiobjective optimization,Multiobjective graph mining,Multiobjective evolutionary programming,Subdue

论文评审过程：Received 1 August 2012, Revised 16 November 2012, Accepted 14 March 2013, Available online 19 March 2013.

论文官网地址：https://doi.org/10.1016/j.jcss.2013.03.005