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Parallel acceleration method for multi-mode graph matching

A pattern diagram and multi-pattern technology, applied in other database indexing, other database retrieval, etc., can solve the problem that there is no parallel processing method for structural correlation pattern diagrams, and achieve the effect of improving matching performance, improving efficiency, and improving performance

Active Publication Date: 2019-04-12
INST OF INFORMATION ENG CAS
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AI Technical Summary

Problems solved by technology

However, the existing multi-pattern graph matching technology is not mature enough, and there is no efficient parallel processing method for schema graphs with weak structural correlations, and the performance of multi-pattern graph matching technology needs to be improved.

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  • Parallel acceleration method for multi-mode graph matching
  • Parallel acceleration method for multi-mode graph matching
  • Parallel acceleration method for multi-mode graph matching

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Embodiment Construction

[0045] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, and to make the purpose, features and advantages of the present invention more obvious and understandable, the technical core of the present invention will be further described in detail below in conjunction with the accompanying drawings . It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0046] The parallel matching algorithm proposed by the present invention mainly includes four key processes: multi-pattern graph index construction, schema graph heuristic grouping, schema graph parallel matching, and "parallel+serial" matching optimization strategy. The algorithm will be analyzed from these four parts below for details.

[0047] Process 1: Multi-mode graph index construction

[0048] A tree-type index structure Pattern Tree based ...

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Abstract

The invention discloses a parallel acceleration method for multi-mode graph matching. The method comprises the following steps: 1) generating a multi-mode graph index of a mode graph set of a target domain; 2) adopting a layer-by-layer grouping strategy for the multi-mode graph index, namely evaluating the mode graph appearing in each layer in the multi-mode graph index to obtain the matching costof mode graphs in each layer, and then grouping the mode graphs of the layer according to the matching cost; and 3) respectively allocating threads to different groups and simultaneously carrying outmatching calculation. According to the method, the structural correlation among the pattern graphs is mined by adopting a Pattern Tree index construction algorithm, and a parallel matching strategy is designed for the pattern graph with relatively weak structural correlation, so that the matching performance is further improved.

Description

technical field [0001] The invention proposes a parallel acceleration method for multi-mode graph matching, which belongs to the technical field of computer software. Background technique [0002] In the era of big data, the scale of data continues to expand, the structure of data is increasingly complex, and the correlation between data is closer. These characteristics bring great challenges to big data analysis. As a widely used data structure, graphs can effectively describe closely related data. Practical problems in many fields can be transformed into computational problems on graphs, such as image analysis, biological data analysis, social network analysis, privacy protection, etc. Graph Pattern Matching Technology (Graph Pattern Matching Technology) is an important means to solve the above complex graph data analysis and mining problems through the efficient query of large-scale graph data. It has become a problem that has been widely concerned by academia and industr...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/901
Inventor 于静郭晶晶刘小梅刘燕兵曹聪谭建龙郭莉
Owner INST OF INFORMATION ENG CAS
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