Cross-commodity-category commodity recommendation method and device

Abstract

The invention discloses a cross-commodity-category commodity recommendation method and device. The method comprises the steps that user transaction data including first commodity information are acquired; a pre-established commodity association data table is queried according to the user transaction data to acquire at least one second commodity information which is associated with the first commodity information and belongs to a different commodity category, wherein the commodity association data table is acquired by statistical analysis based on commodity transaction historical data; and commodity recommendation is carried out according to at least one second commodity information. The association relationship of cross-commodity-category commodity information is established by pre-establishing the commodity association data table. The commodity association data table is queried to acquire at least one second commodity information which is associated with the first commodity information and belongs to a different commodity category, and cross-commodity-category commodity recommendation is realized. Barriers between different commodity categories are broken, and the purchase rate ofrecommended commodities is improved.

Description

technical field [0001] The present invention relates to the field of software, in particular to a product recommendation method and device across product categories. Background technique [0002] Commodity recommendation can use various promotion methods and various channels to guide users to target stores or websites. When recommending products, you can publish product advertisements through some advertising platforms on the Internet, or through the exchange of product advertisements between merchants, use various channels to promote product information, and let users who need it seen in order to ultimately drive the user to make a purchase. Recommending products can greatly increase the amount of promotion of product information and expand the user group that may purchase. [0003] However, when the prior art implements product recommendation, it is generally based on the fact that the user has purchased or searched for a certain product, and recommends other product inf...

AI Technical Summary

Problems solved by technology

This recommendation method is to directly search for the same product based on the keyword or product category of the product, so that the recommended product that the user sees is of the same category as the product that the user has already purchased, which cannot stimulate the user's desire to continue buying and cannot improve the quality of the product. Purchase rate of recommended products

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