The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Dec. 20, 2022

Filed:

Nov. 26, 2019
Applicant:

Zhejiang University, Hangzhou, CN;

Inventors:

Jianwei Yin, Hangzhou, CN;

Zhiling Luo, Hangzhou, CN;

Zhaohui Wu, Hangzhou, CN;

Shuiguang Deng, Hangzhou, CN;

Ying Li, Hangzhou, CN;

Jian Wu, Hangzhou, CN;

Assignee:

ZHEJIANG UNIVERSITY, Hangzhou, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/90 (2019.01); G06F 16/9038 (2019.01); G06F 16/901 (2019.01); G06K 9/62 (2022.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G06F 17/16 (2006.01);
U.S. Cl.
CPC ...
G06F 16/9038 (2019.01); G06F 16/9024 (2019.01); G06K 9/6261 (2013.01); G06K 9/6276 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06F 17/16 (2013.01);
Abstract

A method and system of graph feature extraction and graph classification based on adjacency matrix is provided. The invention first concentrates the connection information elements in the adjacency matrix into a specific diagonal region of the adjacency matrix which reduces the non-connection information elements in advance. Then the subgraph structure of the graph is further extracted along the diagonal direction using the filter matrix. Further, it uses a stacked convolutional neural network to extract a larger subgraph structure. On one hand, it greatly reduces the amount of computation and complexity, getting rid of the limitations caused by computational complexity and window size. On the other hand, it can capture large subgraph structure through a small window, as well as deep features from the implicit correlation structures at both vertex and edge level, which improves speed and accuracy of graph classification.


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