Commodity object recommendation method and device, computer equipment and storage medium

Abstract

The invention discloses a commodity object recommendation method and device, equipment and a medium, and the method comprises the steps: verifying the historical on-sale state information of a current commodity object in a list of the current commodity object, confirming the on-sale state of the current commodity object in each independent transaction site of a plurality of seller users in a set historical time period, wherein more than two independent transaction sites of one seller user are all in an on-sale state; according to respective geographic position information of a plurality of seller users of which commodity objects are in a sold state in an independent transaction site, confirming that the seller users are in the same geographic area; verifying and confirming that the current commodity object presents a rising trend in the same specific ranking list data in a set recent period; and determining all the confirmed current commodity objects as recommendable commodity objects, and pushing the recommendable commodity objects to the seller user to which the at least one independent transaction site belongs. According to the method, the advantage of performing data mining on big data can be fully utilized, and hot-sell commodities suitable for recommendation can be more accurately determined.

Description

technical field [0001] The embodiments of the present application relate to the technical field of the Internet, in particular, a commodity object recommendation method, device, computer equipment, and storage medium. Background technique [0002] At present, the mainstream e-commerce platform has only split data such as sales volume and sales to measure the popularity of commodities. The degree of commodity popularity only has functions such as sales, sales from high to low, and from low to high. There are only hot-selling tags, but without considering the geographical restrictions and the trend period of the real-time search of the corresponding products on the search engine platform. The above-mentioned existing product object recommendation method is designed and calculated based on the above-mentioned conventional indicators, but for the hot-selling explosive products. There is currently no effective method for analysis and positioning, so it is not suitable for indepen...

AI Technical Summary

Problems solved by technology

[0002] At present, the mainstream e-commerce platform has only split data such as sales volume and sales to measure the popularity of commodities. The degree of commodity popularity only has functions such as sales, sales from high to low, and from low to high. There are only hot-selling tags, but without considering the geographical restrictions and the trend period of the real-time search of the corresponding products on the search engine platform. The above-mentioned existing product object recommendation method is designed and calculated based on the above-mentioned conventional indicators, but for the hot-selling explosive products. There is currently no effective method for analysis and positioning, so it is not suitable for independent website sellers in different regions

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