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

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 proble...

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Vydáno v:Journal of combinatorial optimization Ročník 49; číslo 1; s. 9
Hlavní autoři: Yoon, SeongCheol, Seo, Daehee, Kim, Su-Hyun, Lee, Im-Yeong
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Springer US 01.01.2025
Springer Nature B.V
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ISSN:1382-6905, 1573-2886
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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 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 . When generating 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 generation algorithm that prevents generating unnecessary walk and applies it to existing algorithms to prevent the tottering.
AbstractList 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 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 . When generating 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 generation algorithm that prevents generating unnecessary walk and applies it to existing algorithms to prevent the tottering.
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.
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 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. When generating 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 generation algorithm that prevents generating unnecessary walk and applies it to existing algorithms to prevent the tottering.
ArticleNumber 9
Author Yoon, SeongCheol
Lee, Im-Yeong
Kim, Su-Hyun
Seo, Daehee
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  fullname: Seo, Daehee
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  givenname: Su-Hyun
  surname: Kim
  fullname: Kim, Su-Hyun
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  organization: Soonchunhyang University
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  givenname: Im-Yeong
  surname: Lee
  fullname: Lee, Im-Yeong
  organization: Soonchunhyang University
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Heuristic algorithm
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Snippet Graph edit distance is usually used for graph similarity checking due to its low information loss and flexibility advantages. However, graph edit distance...
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SubjectTerms Algorithms
Approximation
Combinatorics
Convex and Discrete Geometry
Graphs
Heuristic
Heuristic methods
Mathematical Modeling and Industrial Mathematics
Mathematics
Mathematics and Statistics
Nodes
Operations Research/Decision Theory
Optimization
Theory of Computation
Title A study on k-walk generation algorithm to prevent the tottering in graph edit distance heuristic algorithms
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