Optimized method of commodity recommendation based on e-commerce platform management

Abstract

The invention specifically relates to an optimized method of commodity recommendation based on e-commerce platform management; it comprises the following steps of: marking the product classificationson the e-commerce platform as fast moving consumer goods and consumer durables; recommending products to users according to the search records of the users, which specifically comprises: determining which of the fast moving consumer goods, the consumer durables, and the user-interested products are searched for, and if it is a fast moving consumer product, the product of the same type as the product is always recommended; In the case of a consumer durable product, the same type of item as the searched item is recommended before the user purchases the searched item. The fast moving consumer goods such as tissue, paper, towel, liquid detergent and the like are fast in consumption and high in purchase frequency, so in this case, it is appropriate to always recommend to the user to improve theuser experience; the consumer durables, such as a computer, a mobile phone, an electric toothbrush and the like, are durable in use time and low in purchase frequency, so that it is not appropriate to recommend them to the user again after purchasing the searched product, otherwise it will damage the user experience, and it is not conducive to promoting consumption.

Description

technical field [0001] The invention relates to the field of social network and information security, in particular to a product recommendation optimization method based on e-commerce platform management. Background technique [0002] Since the 1990s, China has set off a wave of informatization, and China's e-commerce has also started since then. Up to now, Internet information fragmentation and cloud computing technology have become more mature, and active Internet marketing models have emerged. i-Commerce ( Individual Commerce) took advantage of the trend, and e-commerce got rid of the current situation that the traditional sales model was born on the Internet, and communicated with users in depth from multiple angles such as initiative, interaction, and user care, especially the emerging various search and purchase habits based on users. The recommendation algorithm is more than cool but lacks user experience. For example, user a purchases product A. After opening the e-c...

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