Graph neural network GAT-based patent valuation method and system for click auction website

A neural network and patented technology, which is applied in the patent valuation and system field based on the graph neural network GAT of Dianpai.com, can solve the problem of incomplete evaluation and achieve the effect of accurate value

Inactive Publication Date: 2020-09-29
山东佳联电子商务有限公司 +1
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the deficiencies of the prior art, the present invention provides a patent valuation method and system based on graph neural network GAT of Dianpai

Method used

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  • Graph neural network GAT-based patent valuation method and system for click auction website
  • Graph neural network GAT-based patent valuation method and system for click auction website
  • Graph neural network GAT-based patent valuation method and system for click auction website

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Embodiment 1

[0036] A patent valuation method based on graph neural network GAT of Dianpai.com, comprising the following steps;

[0037] Obtain the patent training data set (1000 pieces), the basic information parameters of the patents to be evaluated include patent application number, title, industry classification, first inventor, number of cited patents, number of cited patents, estimated expiration date, current application / Patentee, original application / patentee, number of citations within 3 years, number of citations within 5 years, legal status, simple legal status;

[0038] The attribute parameters of each patent data include: Patent Stability-Novelty, Patent Stability-Creativity, Patent Stability-Writing Quality, Patent Stability-Scope of Protection, Patent Family, Dependency, Technology-Technology Originality, Technology- Technology life cycle, technology-irreplaceability, economy-market share, economy-policy orientation, economy-market demand;

[0039] Use the attention graph ...

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PUM

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Abstract

The invention provides a graph neural network GAT-based patent valuation method and system for a click auction website, and relates to the field of evaluation methods. The weights of the patent attribute parameters in a training data set are trained by using an attention graph neural network GAT, a patent valuation model is abstracted into a knowledge graph, an assessed value of the patent value is taken as a Root of the graph, an attribute parameter related to the patent valuation is taken as a neighbor node of the root, and an edge between the Root and the Node represents a weight coefficient W between the parameter and the assessed value; and the weight coefficient W is trained by using the GAT, after W is trained, a test data set is input, and the evaluation value of each patent data in the test data set can be obtained by multiplying the value of each attribute parameter node in the test data set by the corresponding weight. The weight value is obtained by utilizing big data, andthe value of the patent is integrally evaluated and confirmed, so that the value of patent evaluation is more accurate.

Description

technical field [0001] The invention relates to a patented evaluation method and system based on graph neural network GAT of Dianpai.com, which belongs to the technical field of evaluation methods. Background technique [0002] The patent value analysis index system is a set of index groups that can reflect the overall characteristics of the value of the patent being evaluated, and has internal connections and complementary functions. It is an objective reflection of the intrinsic value of the patent in the transaction. A reasonable and complete index system is a prerequisite for evaluating and analyzing the value of patents. [0003] In Dianpai.com's current patent value evaluation system, the weight ratio of each parameter of the patent valuation model is obtained by analyzing human experience. It is more accurate for a specific field but not applicable to other fields, resulting in the true value of the patent. The difference from the appraised value is too large. In ad...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/18G06N3/04G06N3/08
CPCG06Q10/06393G06Q50/184G06N3/08G06N3/047G06N3/045
Inventor 陈伟李维新李丽华
Owner 山东佳联电子商务有限公司
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