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A fast labeled graph matching algorithm based on edge matching and guided by search route

机译:基于边缘匹配和搜索路线引导的快速标记图匹配算法

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This paper presents a fast labeled graph matching algorithm called graph explorer (GE) algorithm, which can be categorized into the tree search based graph matching (TSGM) algorithms of exact graph/subgraph matching. Not like the other node-centric TSGM algorithms, the GE algorithm focuses on edges matching. It constructs search state of partially matched subgraph by edge and edge. It converts graph matching problem into a path search problem in the space of search states. Under the guidance of the search path, it avoided repeated label checking by inheriting state tree structure for caching and fast visiting matched nodes and edge. By a carefully optimized search route and intelligent backtracking, GE algorithm avoided a large amount of the invalid search states and improved performance to be almost linear to the number of edges of pattern graph with low ambiguity. While traditional TSGM are suffering the call stack overflow problem caused by recursive function calls, it overcame this problem by a dynamic state queue. It can handle extra large size of pattern (up to 10,000 nodes). The experiment shows the performance of GE is better than similar algorithms and it is more resistant to ambiguities.
机译:本文介绍了一种名为Graph Explorer(GE)算法的快速标记的图形匹配算法,可以将其分类为基于树搜索的图形匹配(TSGM)算法的精确图形/子图匹配。不像其他以其他中心为中心的TSGM算法,GE算法侧重于边缘匹配。它通过边缘和边缘构造部分匹配的子图的搜索状态。它将图形匹配问题转换为搜索状态空间中的路径搜索问题。在搜索路径的指导下,它避免了通过继承状态树结构来避免重复标签检查,以便缓存和快速访问匹配节点和边缘。通过仔细优化的搜索路线和智能回溯,GE算法避免了大量无效的搜索状态,并改善了具有低歧义的图案图的边缘的几乎线性的性能。虽然传统的TSGM正在遭受递归函数调用引起的呼叫堆栈溢出问题,但它通过动态状态队列克切此问题。它可以处理超大尺寸的模式(最多10,000个节点)。实验表明,GE的性能优于类似的算法,它更耐用含糊不清。

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