Agricultural product network marketing perception quality analysis method and system based on a knowledge graph

CN122115083AActive Publication Date: 2026-05-29HUNAN INST OF INFORMATION TECH

Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
HUNAN INST OF INFORMATION TECH
Filing Date
2026-04-30
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing methods for evaluating the perceived quality of agricultural products sold online have failed to effectively eliminate differences in user rating habits, resulting in distorted evaluation results that cannot accurately reflect the true perceived quality of agricultural products.

Method used

A knowledge graph-based approach is employed, using sentiment analysis to construct user rating bias parameters. This allows for personalized calibration and confidence weight fusion, eliminating differences in user rating habits and improving rating accuracy.

Benefits of technology

This approach improves the accuracy and robustness of perceived quality evaluation for online sales of agricultural products by adaptively eliminating differences in user rating habits, ensuring that evaluation results are closer to the actual perceived quality.

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Abstract

The application provides a knowledge graph-based agricultural product online sales perception quality analysis method and system, which comprises the following steps: performing sentiment analysis on user comment texts to obtain original sentiment scores; constructing a knowledge graph of agricultural product online sales perception quality according to a historical comment text set; calibrating the original sentiment scores based on historical score deviation parameters associated with user entities in the knowledge graph to obtain individual perception scores; determining the confidence weight of each user comment according to the statistical distribution of all individual perception scores under the same commodity link; calculating the perception quality score of the agricultural product under the same commodity link according to the confidence weight and the individual perception score; and determining the perception quality trust score of the agricultural product under each brand based on the perception quality scores of the agricultural product under each commodity link and the corresponding brand data. The application can realize adaptive elimination of user scoring habits, thereby improving the accuracy of the evaluation of the perception quality of agricultural product online sales.
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