Frequent sub-graph mining and optimizing method for single uncertain graph

A technology of frequent subgraphs and optimization methods, applied in other database retrieval, network data retrieval, instruments, etc., to achieve the effect of filling the technical gap

Inactive Publication Date: 2015-09-09
NAT UNIV OF DEFENSE TECH
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Problems solved by technology

[0006] In view of the lack of frequent subgraph mining and optimization technical solutions for a single uncertain graph in the prior art, the purpose of the present invention is to propose a frequent subgraph mining and optimization method for a single uncertain graph, which can allow Determine the graph to mine frequent subgraphs and optimize the mining algorithm, which fills the technical gap in this field

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  • Frequent sub-graph mining and optimizing method for single uncertain graph
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  • Frequent sub-graph mining and optimizing method for single uncertain graph

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Embodiment Construction

[0042] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be further clearly, completely and detailedly described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described The embodiments are only some of the embodiments of the present invention, not all of them. All other embodiments obtained by persons of ordinary skill in the art based on the embodiments of the present invention belong to the protection scope of the present invention.

[0043] A certain graph G is a tuple (V G ,E G , l G , Σ G ), where V G is the set of nodes, is the set of edges, l G :V G ∪E G →Σ G is a function that assigns labels to nodes and edges. |V G |and|E G | represents the number of nodes and edges in G, respectively. For simplicity of description, we assume that the graph is undirected and has no self-loops...

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Abstract

The invention discloses a frequent sub-graph mining and optimizing method for a single uncertain graph. The frequent sub-graph mining and optimizing method comprises: acquiring the single uncertain graph; enumerating all sub-graphs of the single uncertain graph according to the single uncertain graph; using part of implication graphs in all implication graphs of the single uncertain graph as sample graphs by appointing; respectively calculating an existence probability of each sample graph of the single uncertain graph by using a calculation reuse method, and calculating an expected support degree of each sub-graph on the corresponding sample graph of the single uncertain graph by using the calculation reuse method; judging whether the sub-graphs are frequent sub-graphs according to the expected support degree of each sub-graph on the corresponding sample graph of the single uncertain graph and the existence probability of each sample graph of the single uncertain graph; and outputting all the frequent sub-graphs.

Description

technical field [0001] The invention relates to graph mining technology, in particular to a frequent subgraph mining and optimization method for a single uncertain graph. Background technique [0002] Uncertainty is an inherent property in real-world applications, whether for internal or external sources. For example, in a cooperative social network, we may not be able to clearly assert that Bill and Matthew have a good cooperative relationship using the currently available information, and we usually use probability to measure the possibility of such a cooperative relationship. Assuming that the probability of such a relationship exists is p, the value of p is manually determined by experts in the field from the available information, or is automatically generated by information extraction or generation rules. In today's era of big data, there is a stronger demand for managing uncertain data, so there are various data of different quality. In particular, we focus on uncer...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/958G06Q50/01
Inventor 唐九阳赵翔陈一帆李瑞琪
Owner NAT UNIV OF DEFENSE TECH
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