Commodity optimization recommendation method and system for self-built welfare mall

Abstract

The invention relates to a commodity optimization recommendation method and system for a self-built welfare mall. The method comprises the steps of inputting the name of a commodity to be purchased into a shopping APP search box; selecting certain attributes of the commodity, and endowing the commodity with corresponding weights according to the attributes of the commodity; judging similarity values between the similar commodities and the attributes of the commodities; according to the weights and the similarity values of the related attributes between the commodities, calculating the similarity between every two similar commodities is calculated through weighted summation; and respectively comparing the similarities among the similar commodities, and recommending a plurality of commodities with the highest similarity to consumers. According to the method, commodities with higher similarity can be accurately recommended according to the search records and the browsing records of the user, the weights of related attributes can be flexibly adjusted, welfare commodities are recommended in a more targeted mode, and shopping of consumers is more convenient, faster and more accurate.

Description

Technical field[0001]The invention belongs to the field of Internet technology, and specifically relates to a method and system for optimizing and recommending commodities for self-built welfare malls.Background technique[0002]With the continuous development and adjustment of the social economy, all kinds of commodities are flocking (domestic products, foreign products, counterfeit products, etc., commodity types involve all aspects). With the continuous influx of commodities, it is closely related to shoppers. In the past, shopping was almost always done by shoppers going to the malls, comparing between shopping malls, and then buying, physical store shopping is very limited. On the one hand, consumers are exhausted physically and mentally while shopping, on the other hand they can only Confined to a certain area to purchase, the purchased goods are relatively single, but the emergence of online shopping in the past decade has set off a frenzy of online shopping for consumers.[0003...

AI Technical Summary

Problems solved by technology

[0004] However, the current online shopping apps (Taobao, Jingdong, Vipshop, etc.) have obvious defects, that is, when shoppers buy their favorite products, they search for keywords in the search box and then get recommended products. The list of products for consumers is huge, and the similarity between the products cannot be guaranteed. Faced with such a large number of products, it brings shopping difficulties to shoppers, that is, shoppers cannot buy their favorite products in a timely and accurate manner. As a result, the procedures for returning and exchanging goods will be increased in the future, which will bring more changes to consumers.

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