Automatic retail commodity pricing method based on artificial intelligence
By adopting multi-dimensional data acquisition and fine data cleaning in retail product pricing methods, combining matching algorithms and dynamic thresholding mechanisms, the problem of low data accuracy is solved, and the accuracy and market sensitivity of the pricing model are improved.
CN120146892APending Publication Date: 2025-06-13SHANGHAI YINGNEI ENWEN ARTIFICIAL INTELLIGENCE TECHNOLOGY CO LTD
View PDF 0 Cites 0 Cited by
Patent Information
- Application Number
- CN202510239826.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-03
- Publication Date
- 2025-06-13
Smart Images
Figure CN120146892A_ABST
Abstract
The invention discloses an automatic retail commodity pricing method based on artificial intelligence, and the method comprises the following steps: collecting the recognition data and corresponding sales data of a commodity from various data sources; judging whether the collected sales data of all the commodities belong to the same target retail commodity or not according to the identification data, and putting the identification data and the sales data belonging to the same target retail commodity into a database according to an identification result; extracting statistical characteristics related to pricing of the target retail commodity from sales data of a database; constructing a machine learning model for pricing the target retail commodity, and training the model; and inputting the latest sales data of the current target retail commodity, predicting the price of the target retail commodity, and generating an automatic pricing scheme. The method can achieve the dynamic adjustment of the price, quickly responds to the market change, and improves the scientificity and accuracy of pricing.
Need to check novelty before this filing date? Find Prior Art