Graph data-oriented pattern recognition method fusing topological feature

A topology feature and pattern recognition technology, applied in the field of pattern recognition oriented to graph data, can solve the problem of not taking into account the global features of the local topology attributes of the graph, and achieve good application value and improve the effect of accuracy.

Active Publication Date: 2019-03-29
SHANGHAI JIAODA INTELLECTUAL PORPERTY MANAGEMENT CO LTD
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  • Claims
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Problems solved by technology

This method can be applied to graph data of different sizes, but it does not take into account the local topological properties of the graph and the global characteristics of the graph.

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  • Graph data-oriented pattern recognition method fusing topological feature
  • Graph data-oriented pattern recognition method fusing topological feature
  • Graph data-oriented pattern recognition method fusing topological feature

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Embodiment Construction

[0039] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0040] Such as figure 1 As shown, a kind of graph data-oriented pattern recognition method of fusing topological features provided by the present invention includes:

[0041] Graph conversion step: rebuild the graph data stored in the form of database or file in the form of graph in memory;

[0042] Data preprocessing step: project the graph data in the memory into the vector space and convert it into a set of fixed-size feature tensors and feature vectors through feature extraction;

[0043] Neural n...

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Abstract

The invention provides a graph data-oriented pattern recognition method fusing topological features, which comprises the following steps: graph conversion steps: reconstructing graph data stored in adatabase or a file form in a memory in a graph form;a data preprocessing step: projecting the graph data in the memory into the vector space and converting the graph data into a set of fixed-size feature tensors and feature vectors through feature extraction; a neural network step: the neural network is used to train and classify the feature tensor and feature vector. By extracting the local topological feature quantities of each node in the receptive field and the global topological feature quantities of the graph, the invention enables the input of the neural network to have a clearer description of the topological structure and the feature of the graph, thereby improving the accuracy of the pattern recognition oriented to the graph data.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a graph data-oriented pattern recognition method for merging topological features. Background technique [0002] As human society enters the information age, the status of data has become more and more important. Nowadays, at every moment, countless pieces of data are generated in the world and spread around the world with the help of Internet technology. The massive scale of data and the complexity and diversification of content and structural forms make it increasingly difficult for ordinary structured data forms to support people's diverse needs. In order to better express the relationship between data, people began to try to use the graph structure to represent data. A graph is a powerful data representation. The nodes and edges with attributes it contains can display the internal relationship between different entities in an intuitive and general way, thereby const...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/24
Inventor 陈俊陈昊鹏
Owner SHANGHAI JIAODA INTELLECTUAL PORPERTY MANAGEMENT CO LTD
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