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Commodity recommendation method based on model matching

A product recommendation and product technology, applied in the computer field, can solve the problem of not considering the internal relationship between products and users.

Inactive Publication Date: 2012-07-04
BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

[0005] Content-based recommendation and collaborative recommendation reflect the user's shopping needs in different aspects, but the above-mentioned recommendation methods do not take into account the internal relationship between the product and the user.

Method used

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  • Commodity recommendation method based on model matching
  • Commodity recommendation method based on model matching
  • Commodity recommendation method based on model matching

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Embodiment Construction

[0032] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0033] figure 1 The steps of the product recommendation method based on model matching are shown, mainly including:

[0034] Step S100, establishing a commodity model. The commodity model is expressed as:

[0035] G = {GSyno, GAttr}

[0036] Among them, GSyno is a thesaurus obtained after lexical analysis of a paragraph of text describing the product, and GAttr is the attribute of the product, which consists of multiple [Key, Value] key-value pairs, one of which corresponds to A Value collection. The description of the product comes from the written material or webpage introduction material provided by the supplier or manufacturer. Commodity attributes adopt the directory structure attributes of e-commerce websites, and at the same time add various information such as place of origin, supplier, etc., and commodity attributes can be expanded...

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Abstract

The invention discloses a commodity recommendation method based on model matching, which mainly comprises the following steps of: establishing a commodity description model, wherein the commodity description model comprises two parts, i.e. a character introduction and description part and an attribute information part; establishing a user preference model, ensuring that the user preference model is based on the commodity description model and fusing a plurality of commodity description models through the user preference model; calculating the similarity between the commodity description model and the user preference model; and ranking according to the similarity to recommend to a user. According to the commodity recommendation method, the potential interest of the user can be fully explored, and the accuracy of commodity recommendation can be realized.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a method for recommending commodities based on matching commodity models and user models applicable to e-commerce websites. Background technique [0002] In recent years, with the advancement of computer and network technology, e-commerce has developed rapidly. With its advantages of convenience, speed, low price, and complete categories, e-commerce has seen its market share soar year by year. Large-scale e-commerce websites often sell a large number of products, but the products that can be presented to users on the website pages are limited, so a product recommendation system is often needed, which can recommend the most suitable products to customers according to user preferences. The product recommendation algorithm is the core of the entire product recommendation system, which largely determines the type and performance of the recommendation system. [0003] At present, ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06F17/30
Inventor 韩军
Owner BEIJING JINGDONG SHANGKE INFORMATION TECH CO LTD
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