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Commodity individual recommendation method for new users and system

A recommendation method and recommendation system technology, applied in the field of data processing, can solve the problem of low recommendation accuracy

Inactive Publication Date: 2015-12-23
GUANGZHOU PINWEI SOFTWARE
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Based on this, it is necessary to provide a personalized product recommendation method and system for new users with improved recommendation accuracy for the problem of low recommendation accuracy.

Method used

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  • Commodity individual recommendation method for new users and system
  • Commodity individual recommendation method for new users and system
  • Commodity individual recommendation method for new users and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0026] see figure 1 , providing an embodiment of a method for personalized product recommendation for new users, including the following steps:

[0027] S100: Obtain historical commodity data, and record the attribute characteristics of the historical commodity and the sales volume of the historical commodity in the historical commodity data according to the historical commodity data.

[0028] When a user visits a webpage to purchase a product, relevant data of the purchased product will be generated, thereby generating historical product data. According to the historical product data, the attribute characteristics and sales volume of the historical product are recorded, and the attribute characteristics and sales volume of the historical product are obtained. for subsequent inquiries and use.

[0029] S200: According to the attribute characteristics of the historical commodities and the sales volume of the historical commodities, obtain the corresponding relationship between...

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Abstract

The invention relates to a commodity individual recommendation method for new users and a system. The method comprises the following steps: specific to the new users having no corresponding attributive character of a purchase commodity, acquiring a relationship between the attributive character of the commodity and the sales volume of the commodity by taking the sales volume of the commodity as a forecast target according to the recorded historic attributive character of the commodity; forecasting the sales volume of the to-be-recommended commodities according to the relationship between the attributive character of the commodity and the sales volume of the commodity; ranking the to-be-recommended commodities; performing individual recommendation according to a ranking result. The forecast target is arranged as the sales volume, so that the quantity of the new users purchasing the commodities is considered instead of the sales volume contributed by the new users; for the new users contributing to the webpage visiting volume, the motivation for arranging the forecast target is clearer; accurate recommendation can be performed and a better recommendation effect is achieved.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method and system for personalized commodity recommendation for new users. Background technique [0002] The existing recommendation model is aimed at regular customers, and the model prediction target is sales. According to the purchase history of regular customers, recommend products that they are interested in to different users. That is to say, the existing recommendation model is aimed at regular customers and uses historical and real-time data to train the model. The prediction goal of the training data is sales, that is, the goal is to maximize sales. The model training results output the sales of each commodity, and according to the sales, output the ranking of the commodities to achieve the purpose of personalized recommendation for users. [0003] The existing product recommendation model is aimed at old users, and the prediction target of the model is sales....

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02
Inventor 雷迦吟
Owner GUANGZHOU PINWEI SOFTWARE
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