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A covariance-based product recommendation method

A product recommendation and covariance technology, applied in the field of product recommendation based on covariance, can solve problems such as difficult user selection, and achieve the effect of solving difficult user selection

Active Publication Date: 2022-07-12
CHENGDU UNIVERSITY OF TECHNOLOGY
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Aiming at the above-mentioned shortcomings in the prior art, a covariance-based product recommendation method provided by the present invention solves the problem of difficult selection for users due to information overload in e-commerce

Method used

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  • A covariance-based product recommendation method
  • A covariance-based product recommendation method
  • A covariance-based product recommendation method

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Embodiment Construction

[0033] The specific embodiments of the present invention are described below to facilitate those skilled in the art to understand the present invention, but it should be clear that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, as long as various changes Such changes are obvious within the spirit and scope of the present invention as defined and determined by the appended claims, and all inventions and creations utilizing the inventive concept are within the scope of protection.

[0034] like figure 1 As shown, the covariance-based product recommendation method includes the following steps:

[0035] S0. Eliminate other types of items according to the user's screening conditions, and keep items that meet the user's screening conditions;

[0036] S1. Obtain the number of times each user purchased each item, and obtain the initial behavior vector of each user;

[0037] S2. Obtain the covariance value of the pairwise ...

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Abstract

The invention discloses a covariance-based product recommendation method, which includes the following steps: S1. Obtain the number of times each user purchases each item and the initial behavior vector of each user; S2. Obtain any item and each item The covariance value of the pairwise correlation between them; S3. Obtain the covariance matrix based on the item; S4. Obtain the recommended value of the item according to the initial behavior vector and the covariance matrix; S5. For any user, remove the user's The purchased items and their corresponding recommended values ​​are sorted, and the remaining items are sorted according to the size of the recommended value given by the user to obtain a product recommendation list for the user. The invention fully considers the randomness of the user's purchasing behavior, applies the covariance to the field of commodity recommendation, and makes the recommended commodity more in line with the needs of each user according to the user's historical behavior, and effectively solves the problem of user selection caused by information overload in e-commerce. difficult question.

Description

technical field [0001] The invention relates to the field of commodity recommendation, in particular to a covariance-based commodity recommendation method. Background technique [0002] With the development of e-commerce, more and more people devote themselves to e-commerce, which makes e-commerce develop vigorously, but for users, information overload is the biggest problem. Take Taobao as an example: when a user enters the desired product to search during the online shopping process, there will be a large number of the same product for the user to choose from. At this time, the user may encounter the problem of difficult selection. Usually, the situation is: cheap but Worry about quality; both worry about quality and feel expensive, which makes it difficult for users to choose items when selecting items, which is also the problem caused by information overload. Therefore, how to find the goods that users need from a large number of goods is an urgent need for e-commerce so...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q30/06
CPCG06Q30/0631
Inventor 蔡彪黄玉盛杨小王
Owner CHENGDU UNIVERSITY OF TECHNOLOGY