Commodity recommendation method and system based on big data
A product recommendation and big data technology, applied in data processing applications, commerce, instruments, etc., can solve problems such as blinding buyers, complex search functions, product name image user search results, etc., to increase frequency, improve industry standards, and comprehensively The effect of product reviews
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Embodiment 1
[0067] Such as figure 1 As shown, this embodiment provides a method for recommending commodities based on big data, including the following steps:
[0068] a) Obtain the first account information for logging into the current e-commerce platform;
[0069] b) Obtain the first product information selected by the user, and extract keywords included in the first product information, where the keywords include product name and product use;
[0070] c) Obtaining all second account information that has a friend relationship with the first account information in the e-commerce platform;
[0071] d) Extract the shopping record of the second account information, the shopping record includes a number of second product information, and the second product information includes product name, product use, product price and product evaluation;
[0072] e) judging whether keywords exist in the second product information;
[0073] f) If yes, extract the second product information including key...
Embodiment 2
[0079] Such as figure 2 As shown, the shopping record from which the second account information is extracted also includes:
[0080] Judging whether the product use included in the second product information is consistent with the product use included in the keyword;
[0081] If so, extract the second product information that is consistent with the product use in the keyword;
[0082] The second product information is exported to the first account information.
[0083] Obtaining all the second account information that has a friend relationship with the first account information in the e-commerce platform includes:
[0084] Obtain social software on the user's device;
[0085] Obtain the third account information on social software that has a friend relationship with the user;
[0086] Obtain the fourth account information that has a binding relationship with the third account information in the e-commerce platform;
[0087] Commodity recommendation is performed using the...
Embodiment 3
[0091] Such as Figure 4 As shown, the extracted product price and product evaluation in the second product information include:
[0092] Obtain the first favorable rating of the first product information on the e-commerce platform;
[0093] Obtain the second favorable rate of the second product information of the second account information, and the second favorable rate is an average value;
[0094] Judging whether the difference between the first favorable rate and the second favorable rate is within a preset range;
[0095] If not, the first product information is specially marked.
[0096] Extracting the product price and product evaluation in the second product information also includes:
[0097] Obtain the first account information and the second account information;
[0098] Outputting the first account information and the second product information to the second account information;
[0099] Obtain the detailed evaluation filled in by the second user;
[0100] Th...
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