Article identification method and device

Abstract

The invention discloses an article identification method and device, and relates to the field of warehouse logistics. A specific embodiment of the method comprises the steps of determining a contribution type of each article in an activity according to an introduction flow and a sales volume of each article in the activity; obtaining feature information of each article in the plurality of activities, and inputting the feature information, the sales volume, the introduction flow and the contribution type of each article in each activity into a to-be-trained model for training to obtain a non-contribution article recognition model; and processing the feature information of each to-be-processed article by using the non-contribution article identification model so as to identify an article of which the contribution type is non-contribution. According to the embodiment, the model is trained based on the feature information of contributed and non-contributed articles and the evaluation variables, and the method and device are finally applied to evaluating which spare articles do not contribute to activities, so that error decisions caused by data randomness in a traditional analysis method are avoided.

Description

technical field [0001] The invention relates to the field of warehousing and logistics, in particular to an item identification method and device. Background technique [0002] In order to increase consumers' willingness to purchase, increase conversion rates and sales, platforms or merchants often set up activities in various forms and discounts. After the activities are over, they will review the results to see if the sales goals have been achieved. Some will also analyze which items are not effective in participating in this event, so the item will be eliminated in the next event. If this review and continuous iterative optimization of the item pool are not carried out, a large number of unattractive items may continue to exist in the item pool, wasting marketing traffic and reducing user experience. [0003] During the activity review and optimization process, procurement and marketing or related analysts usually use simple data analysis combined with subjective experie...

AI Technical Summary

Problems solved by technology

This approach relies too much on the professional capabilities of purchasers and sales personnel, and has the following limitations: 1) The index of concern is single, and the contribution of items cannot be fully evaluated; 2) The principle of item elimination is simple, lacking data support and scientific guidance

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