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The index-based subgraph matching algorithm (ISMA): fast subgraph enumeration in large networks using optimized

Sofie Demeyer1, Tom Michoel, Jan Fostier

  • 1Department of Information Technology, Ghent University, Ghent, Belgium. Sofie.Demeyer@intec.ugent.be

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Summary
This summary is machine-generated.

We developed the Index-based Subgraph Matching Algorithm (ISMA), a novel tree-based method for efficiently finding network motifs. ISMA significantly speeds up subgraph matching in large networks, outperforming existing algorithms.

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Area of Science:

  • Computer Science
  • Graph Theory
  • Network Analysis

Background:

  • Subgraph matching is crucial for identifying network motifs, which are statistically overrepresented subgraph patterns.
  • Existing algorithms face challenges with scalability in large networks.

Purpose of the Study:

  • To introduce a novel, efficient subgraph matching algorithm.
  • To improve the speed and scalability of network motif discovery.

Main Methods:

  • Developed the Index-based Subgraph Matching Algorithm (ISMA), a tree-based approach.
  • Optimized node investigation order and utilized symmetry characteristics.
  • Implemented data structures for efficient subgraph analysis.

Main Results:

  • ISMA demonstrates significant speedup compared to naive and existing subgraph matching algorithms.
  • The algorithm performs exceptionally well on large networks and with large query subgraphs.
  • ISMA outperforms other tested subgraph matching methods.

Conclusions:

  • ISMA offers a substantial improvement for subgraph matching and network motif analysis.
  • The algorithm's efficiency makes it suitable for large-scale network data.
  • A Java implementation of ISMA is publicly available.