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A coding method for efficient subgraph querying on vertex- and edge-labeled graphs.

Lei Zhu1, Qinbao Song1, Yuchen Guo1

  • 1Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China.

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Summary
This summary is machine-generated.

This study introduces a new coding method for subgraph querying using Laplacian spectrum and walk counts. The approach significantly improves query efficiency in labeled graph databases, even with frequent updates.

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Area of Science:

  • Computer Science
  • Graph Theory
  • Database Systems

Background:

  • Labeled graphs are crucial for modeling complex data across various domains.
  • Subgraph querying is essential but computationally expensive due to the NP-complete subgraph isomorphism problem.

Purpose of the Study:

  • To develop a novel, efficient coding method for subgraph querying in labeled graphs.
  • To address the time-consuming nature of subgraph isomorphism testing in large graph databases.

Main Methods:

  • Proposed a new coding technique based on Laplacian spectrum and the number of walks.
  • Implemented a filtering-and-verification framework suitable for dynamic graph databases.
  • Introduced novel two-step filtering conditions ensuring no false negatives.

Main Results:

  • The proposed method effectively filters out most false positives.
  • Demonstrated that the filtering conditions meet the no-false-negative requirement.
  • Experimental results show significant efficiency improvements over six existing methods.

Conclusions:

  • The novel coding method based on Laplacian spectrum and walk counts enhances subgraph querying efficiency.
  • The method is well-suited for graph databases experiencing frequent updates.
  • The two-step filtering conditions provide accurate and comprehensive query results.