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A study on $$k$$ k - $$walk$$ walk generation algorithm to prevent the tottering in graph edit distance heuristic algorithms

Author

Listed:
  • SeongCheol Yoon

    (Soonchunhyang University)

  • Daehee Seo

    (Sangmyung University)

  • Su-Hyun Kim

    (Soonchunhyang University)

  • Im-Yeong Lee

    (Soonchunhyang University)

Abstract

Graph edit distance is usually used for graph similarity checking due to its low information loss and flexibility advantages. However, graph edit distance can’t be used efficiently because it is an NP-Hard problem. Many graph edit distance heuristic algorithms have been proposed to solve this problem. However, some heuristic algorithms for generating $$walk$$ walk generate unnecessary sequences because of the tottering, which leads to many problems. Because of this, various problems arise, like a decrease in approximation accuracy and an increase in execution time. In this paper, we propose an accurate and efficient graph edit distance heuristic algorithm that prevents tottering when generating $$walk$$ walk . When generating $$walk$$ walk , the traversed node‘s information is saved into the queue and then proceeds to traverse the next node. Then, it is possible to prevent the tottering by comparing an existing traversed node with an enqueued one. Through this, we propose a new $$walk$$ walk generation algorithm that prevents generating unnecessary $$walk$$ walk and applies it to existing algorithms to prevent the tottering.

Suggested Citation

  • SeongCheol Yoon & Daehee Seo & Su-Hyun Kim & Im-Yeong Lee, 2025. "A study on $$k$$ k - $$walk$$ walk generation algorithm to prevent the tottering in graph edit distance heuristic algorithms," Journal of Combinatorial Optimization, Springer, vol. 49(1), pages 1-15, January.
  • Handle: RePEc:spr:jcomop:v:49:y:2025:i:1:d:10.1007_s10878-024-01236-5
    DOI: 10.1007/s10878-024-01236-5
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