Commodity recommendation optimizing method based on customer behavior
A product recommendation and optimization method technology, applied in marketing and other directions, can solve problems such as inability to update online, failure to consider customer purchase interest, and delay in updating calculation results, etc., to achieve the effect of solving cold start and personalized recommended products
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[0061] The present invention will be described in detail below in conjunction with specific embodiments.
[0062] reference figure 1 , Is a flow chart of the optimization method for product recommendation based on customer behavior, including steps 1 to 7:
[0063] Step 1: Initialization.
[0064] The customer's purchase interest value for all commodities is initialized. The customer's purchase interest value for all commodity categories is initialized.
[0065] buyInterest(u,s)=clickWeight×clickCount(u,s)+buyWeight×buyCount(u,s)
[0066] buyInterestType(u, Type[s])=typeWeight×buyInterest(u,s)
[0067] In the above formula, buyInterest(u,s) represents the purchase interest of customer u's product s, clickCount(u,s) represents the number of clicks on the recommended product s by customer u, clickWeight represents the weight of the customer’s click on the recommended product, buyCount(u, s), represents the number of customer u's purchases of the recommended product s, buyWeight represent...
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