Intelligent article selection and infringement early warning method based on cross-platform mining and knowledge graph

By using a distributed crawler system and knowledge graph technology, product data is obtained from multiple platforms, and a multi-dimensional knowledge graph is constructed to compare product technical features. This solves the problems of semantic gaps and delayed risk assessment in product selection, and realizes the systematization and automation of intelligent product selection and infringement warning.

CN122347437APending Publication Date: 2026-07-07IMC DIGITAL TECH CO LTD
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Patent Information

Application Number
CN202610448691.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-04-07
Publication Date
2026-07-07

AI Technical Summary

Technical Problem

Existing technologies suffer from a semantic gap between consumer and technical language in product selection and patent infringement risk assessment, leading to biased data analysis. The lack of cross-platform correlation and systematic design variants results in delayed risk assessment and reliance on human experience.

Method used

Product data is acquired from multiple platforms through a distributed crawler system. Natural language processing and time series analysis are used to extract product technical features. A multi-dimensional knowledge graph is constructed for comparison, generating a patent infringement risk assessment value. Based on the graph path analysis, a design avoidance solution is generated.

Benefits of technology

It enables cross-platform data synchronization and mining, improves data reliability and the comprehensiveness of product selection analysis, quantifies patent infringement risks, generates scientific product design avoidance solutions, and improves product selection efficiency and compliance.

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Abstract

The invention relates to the technical field of intelligent product selection, in particular to an intelligent product selection and infringement early warning method based on cross-platform mining and a knowledge graph, which comprises the following steps: acquiring a multi-platform product description text, a user interaction behavior sequence and a market dynamic index; processing and analyzing a product text by using a natural language, extracting a technical feature vector, generating a product popularity index in combination with time sequence analysis, dynamically calculating market saturation according to the market, and fusing to form a product market potential evaluation index; constructing a multi-dimensional product knowledge graph based on the technical feature vectors, and screening candidate products according to the potential indexes; mapping the candidate product technical vectors to a knowledge graph, and quantizing to generate a patent infringement risk assessment value; when the risk exceeds a threshold value, generating a design avoidance scheme based on a technical substitution path in the map and the design variant scheme; and outputting intelligent product selection decision support information. According to the invention, the product selection efficiency and accuracy of the platform are improved.
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