Electronic commerce goods recommendation method based on large data multiple labels
A technology for e-commerce and product recommendation, which is applied in the field of e-commerce product recommendation to achieve the effect of satisfying the shopping experience and improving the click-through rate and popularity
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[0020] In order to make the technical means, creative features, objectives and effects of the present invention easy to understand, the present invention will be further explained below in conjunction with specific embodiments.
[0021] The present invention provides a technical solution: an e-commerce product recommendation method based on big data and multiple tags, including the following steps:
[0022] Step 1. User data collection: used to collect user browsing behaviors, and aggregate all user browsing data;
[0023] Step 2. Construction of purchasing behavior model: through the big data cloud computing platform, according to the user’s past historical browsing, purchase records and the corresponding relationship between the browsing time of different pages, establish training samples of purchasing behavior models with different user characteristic information, according to the purchase Behavior model training samples to establish a regression model between the user and the pur...
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