Commodity recommendation method and system

A commodity recommendation and commodity technology, applied in the fields of instruments, computing, electrical and digital data processing, etc., can solve the problems of low efficiency and large amount of data processing, and achieve the effect of improving processing efficiency, improving accuracy and small amount of data

Active Publication Date: 2017-12-29
ALIBABA GRP HLDG LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] This application provides a product recommendation method and system, which can solve the problems of large amount of data processing and low efficiency when recommending products

Method used

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  • Commodity recommendation method and system
  • Commodity recommendation method and system
  • Commodity recommendation method and system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0045] refer to figure 2 , showing Embodiment 1 of a product recommendation method of the present application, including the following steps:

[0046] Step 101, acquiring product pages of related products that have a link relationship with the product page of the current product.

[0047] The product pages of related products that have a link relationship with the product page of the current product include pages linked from the product page of the current product and pages linked to the product information page of the current product. Among them, the products displayed on the product pages with links often have related relationships in terms of product attributes and functions, so they can be considered as related products. The product page may be a page displaying product information, including a description of the product and link information of related products.

[0048] The page data of the product page contains various elements, such as pictures, videos, URLs linked o...

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Abstract

The present application provides a product recommendation method, which includes the following steps: obtaining a product page of a related product that has a link relationship with the product page of the current product; calculating the first degree of association between the current product and the related product according to the link relationship; The information page related to the current commodity, determining the related commodity that has a co-occurrence relationship with the current commodity in the information page; calculating the second degree of association between the current commodity and the related commodity according to the co-occurrence relationship; according to the first The degree of association and the second degree of association determine a third degree of association between the current product and the related product; based on the third degree of association, a recommended product for the current product is determined. The present application also provides a commodity recommendation system implementing the foregoing method. The product recommendation method and system of the present application can reduce the amount of data processing during product recommendation and improve processing efficiency.

Description

technical field [0001] The present application relates to the technical field of computer data processing, in particular to a product recommendation method and system. Background technique [0002] With the continuous development of e-commerce, more and more users choose to shop online. Users access the e-commerce website through a browser and can conveniently select the commodities they need. In many cases, e-commerce websites will recommend products to users. For example, after a user purchases a certain product, it will recommend products similar to or related to the product. products, discounted products, best-selling products and more. Through product recommendation, on the one hand, the sales volume of e-commerce websites can be increased; on the other hand, active recommendation can avoid unnecessary search requests from users due to frequent search and search, and reduce the burden on the website server. [0003] Generally speaking, current e-commerce websites on ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q30/02G06F17/30
Inventor 刘佳陈维赵文峰孙牧
Owner ALIBABA GRP HLDG LTD
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