Commodity recommendation method and device combining RPA and AI
A product recommendation and product technology, applied in the field of data processing, can solve the problems of high similarity, low conversion rate of recommended product purchase, etc.
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[0036]Example 1:
[0037]In this example, determine the page information that the user is currently browsing. The page information can include page identification information, page content information, page type information, etc., and recommended scene information is determined based on the page information. The recommended scene information can arbitrarily distinguish different recommended scenes. The identification information of the information, for example, can be numbers, letters, or text descriptions. Among them, when the recommended scene information is a text description, the recommended scene information can include "recommended scenes based on product details" and "based on package balance Recommended scene" etc.
[0038]In this example, the product category to be recommended can be determined based on the page information. For example, when the page information is the displayed clothing category, the product category to be recommended is a clothing-related category, and further...
Example
[0040]Example 2:
[0041]In this example, the page information is obtained, the preset correspondence relationship is queried, and the recommended scene information corresponding to the page information is obtained. For example, when the page information is the page identifier, if the page identifier corresponding to the page the user browses is the traffic margin view Page identification, the preset relationship between drinking and drinking is queried, and the corresponding recommended scene information determined is the recommended scene based on the package flow margin.
[0042]In this embodiment, a deep learning model can be trained based on NLP technology, and the input of the deep learning model is page information, and the output is recommended scene information.
Example
[0043]Example three:
[0044]In this example, the current shopping scene information includes current holiday information, for example, if it is Christmas, the recommended scene is a recommended scene based on Christmas.
[0045]Step 102: Determine candidate recommended products corresponding to the recommended scenario information, and determine a sorting strategy set corresponding to the recommended scenario information, wherein the sorting strategy set includes at least one sorting strategy.
[0046]As a possible implementation manner, a corresponding recall strategy set can be determined based on the recommended scenario information, where the recall strategy set includes at least one recall strategy, and the candidate recommended product is determined according to at least one recall strategy included in the recall strategy set, where Since the recommended scenario information is related to the user’s purchase intention, at least one recall strategy determined according to the recommend...
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