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Commodity recommendation method

A product recommendation and product technology, applied in the fields of office automation, instruments, electrical digital data processing, etc., can solve the problems of complexity, different complexity of employee benefit procurement decision-making system, lack of user insight and accumulation, etc., to improve accuracy and individuality Maximize satisfaction, improve efficiency and effectiveness

Pending Publication Date: 2021-01-22
中智关爱通(上海)科技股份有限公司
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AI Technical Summary

Problems solved by technology

[0002] For now, the welfare distribution industry belongs to the human resources market segment, and there is a lack of user insight and accumulation for corporate and employee users in the industry; products tend to be highly personalized and complex; corporate users involve a wide range of industries, and employee welfare procurement decisions in different industries The complexity of the system varies, but all gradually become more complex

Method used

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  • Commodity recommendation method

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Embodiment

[0024] This embodiment provides a product recommendation method, in which users include enterprise users or employee users, and for enterprise users, the steps include:

[0025] 1) Obtain the basic data of enterprise users, the recharge month of enterprise users and the amount issued to employees;

[0026] 2) Based on the basic data of enterprise users, the recharge month of enterprise users and the amount issued to employees, generate enterprise user loss labels and classification labels to which enterprise users belong;

[0027] 3) According to the churn tags of enterprise users and the classification tags of enterprise users, the products are clustered through the hot search word segmentation algorithm and collaborative filtering algorithm;

[0028] 4) According to the results of product clustering, product recommendation is made to enterprise users.

[0029] For employee users, steps are included:

[0030] 1) Obtain the consumption times and consumption types of employee...

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Abstract

The invention relates to a commodity recommendation method, which comprises the following steps: obtaining user data which comprises user basic data and user behavior data; generating a user label according to the user data; clustering the commodities through a hot search word segmentation algorithm and a collaborative filtering algorithm according to the user tags; and recommending commodities tothe user according to a commodity clustering result. Compared with the prior art, welfare distribution is established on the basis of scientific basis, accuracy and personalized satisfaction are greatly improved, and efficiency and effect are improved.

Description

technical field [0001] The present invention relates to the field of product recommendation, in particular to a method for product recommendation. Background technique [0002] For now, the welfare distribution industry belongs to the human resources market segment, and there is a lack of user insight and accumulation for corporate and employee users in the industry; products tend to be highly personalized and complex; corporate users involve a wide range of industries, and employee welfare procurement decisions in different industries The complexity of the system varies, but they all gradually become more complex. Moreover, under a given budget, different industries and even enterprises have different requirements for the implementation of welfare programs, and employees have different preferences for different welfare programs and products. Highly improve service effectiveness and employee satisfaction. Contents of the invention [0003] The purpose of the present inve...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9535G06F40/289G06K9/62G06Q10/10
CPCG06Q10/1057G06F16/9535G06F40/289G06F18/23
Inventor 王婉莹
Owner 中智关爱通(上海)科技股份有限公司
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