Knowledge and Information Systems

, Volume 34, Issue 1, pp 75–108 | Cite as

MOSubdue: a Pareto dominance-based multiobjective Subdue algorithm for frequent subgraph mining

  • Prakash Shelokar
  • Arnaud Quirin
  • Óscar CordónEmail author
Regular Paper


Graph-based data mining approaches have been mainly proposed to the task popularly known as frequent subgraph mining subject to a single user preference, like frequency, size, etc. In this work, we propose to deal with the frequent subgraph mining problem from multiobjective optimization viewpoint, where a subgraph (or solution) is defined by several user-defined preferences (or objectives), which are conflicting in nature. For example, mined subgraphs with high frequency are often of small size, and vice-versa. Use of such objectives in the multiobjective subgraph mining process generates Pareto-optimal subgraphs, where no subgraph is better than another subgraph in all objectives. We have applied a Pareto dominance approach for the evaluation and search subgraphs regarding to both proximity and diversity in multiobjective sense, which has incorporated in the framework of Subdue algorithm for subgraph mining. The method is called multiobjective subgraph mining by Subdue (MOSubdue) and has several advantages: (i) generation of Pareto-optimal subgraphs in a single run (ii) selection of subgraph-seeds from the candidate subgraphs based on all objectives (iii) search in the multiobjective subgraphs lattice space, and (iv) capability to deal with different multiobjective frequent subgraph mining tasks by customizing the tackled objectives. The good performance of MOSubdue is shown by performing multiobjective subgraph mining defined by two and three objectives on two real-life datasets.


Graph-based data mining Frequent subgraph mining Subdue Gaston Multiobjective graph-based data mining Pareto-based multiobjective optimization Evolutionary multiobjective optimization 


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  • Prakash Shelokar
    • 1
  • Arnaud Quirin
    • 1
  • Óscar Cordón
    • 1
    • 2
    Email author
  1. 1.European Centre for Soft ComputingMieresSpain
  2. 2.Department of Computer Science and Artificial Intelligence (DECSAI) and the Research Centre on Information and Communication Technologies (CITIC-UGR)University of GranadaGranadaSpain

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