An e-commerce platform commodity recommendation algorithm

Abstract

The invention discloses an e-commerce platform commodity recommendation algorithm, which comprises the following steps of: 1, obtaining operator original data: obtaining a user and a retrieval recordcopy from an operator big data system, including a user ID, a user number, keyword content, a retrieval date, retrieval times, commodity purchase information and commodity purchase times; The invention discloses an e-commerce platform commodity recommendation algorithm. The method comprises the steps of obtaining information of a user or purchase records of other users for judgment; related commodities are pushed; pushing of regional seasons and hot commodities by the user can be met; In addition, according to the invention, the structure is simple;, if the user does not express enough interest in the information pushed for the first time, the information is pushed for the second time; and according to the current season information and a plurality of pieces of commodity information in theregion where the user is located, the push content is adjusted, so that the problem of inaccurate information during first-time push is solved in time, the commodity selection time of the user is effectively shortened, and the user experience is improved.

Description

technical field [0001] The invention relates to the technical field of product recommendation, in particular to an algorithm for product recommendation on an e-commerce platform. Background technique [0002] With the continuous development of science and technology, the acceleration of social informatization, and the continuous improvement of e-commerce trading platforms, more and more people obtain the commodities they need through online shopping. The types of commodities can be related to people's daily life. It provides great convenience for people's life in all aspects. Due to the wide variety of commodities on various e-commerce platforms, users often need to spend a lot of time to select and find the commodities they need when shopping. Therefore, in order to ensure that various merchants User experience, all provide personalized push services for users. However, the existing commodity push methods generally simply push by obtaining the user’s daily browsing records ...

AI Technical Summary

Problems solved by technology

[0002] With the continuous development of science and technology, the acceleration of social informatization, and the continuous improvement of e-commerce trading platforms, more and more people obtain the commodities they need through online shopping. The types of commodities can be related to people's daily life. It provides great convenience for people's life in all aspects. Due to the wide variety of products on various e-commerce platforms, users often need to spend a lot of time to select and find the products they need when shopping. Therefore, in order to ensure that User experience, all provide personalized push services for users. However, the existing commodity push methods generally simply push by obtaining the user’s daily browsing records or purchase history, and do not personalize the product itself or the user’s personal information. Customization, making push information less accurate

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