Product recommendation method and device, computer storage medium and system
The invention provides a product recommendation method and device, a computer storage medium and a system. The method comprises the following steps: determining a target product potential expected value and a target gradient value of a target user; based on the target product potential expected valu...
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| creator | DING QIANJIN |
| description | The invention provides a product recommendation method and device, a computer storage medium and a system. The method comprises the following steps: determining a target product potential expected value and a target gradient value of a target user; based on the target product potential expected value and the target gradient value, determining a similar user set; in the similar user set, obtaining a plurality of gradient values of each user corresponding to the plurality of to-be-recommended products, and forming a similar user gradient value set by using the plurality of gradient values; and determining at least one recommendation gradient value in the similar user gradient value set, and recommending at least one to-be-recommended product corresponding to the at least one recommendation gradient value to the target user. Therefore, the change trend of products preferred by the target user can be analyzed through the target product potential expected value and the target gradient value, so that the similar us |
| format | Patent |
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The method comprises the following steps: determining a target product potential expected value and a target gradient value of a target user; based on the target product potential expected value and the target gradient value, determining a similar user set; in the similar user set, obtaining a plurality of gradient values of each user corresponding to the plurality of to-be-recommended products, and forming a similar user gradient value set by using the plurality of gradient values; and determining at least one recommendation gradient value in the similar user gradient value set, and recommending at least one to-be-recommended product corresponding to the at least one recommendation gradient value to the target user. 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The method comprises the following steps: determining a target product potential expected value and a target gradient value of a target user; based on the target product potential expected value and the target gradient value, determining a similar user set; in the similar user set, obtaining a plurality of gradient values of each user corresponding to the plurality of to-be-recommended products, and forming a similar user gradient value set by using the plurality of gradient values; and determining at least one recommendation gradient value in the similar user gradient value set, and recommending at least one to-be-recommended product corresponding to the at least one recommendation gradient value to the target user. Therefore, the change trend of products preferred by the target user can be analyzed through the target product potential expected value and the target gradient value, so that the similar us</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2022</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyjEKAjEQRuFtLES9w9hrEXTFVhbFQsTCfgmZXw2YTEgmgrd3EQ9g9Yr3jZvTJQtXp5ThJAREtuolUoA-hMlGJsbLOyxo-KkqMhWVbO8YDPsavqa8iyJMm9HNPgtmv06a-WF_7Y5LJOlRknWI0L47G7Nut8Zs2t3qH_MBxdA2Fg</recordid><startdate>20220603</startdate><enddate>20220603</enddate><creator>DING QIANJIN</creator><scope>EVB</scope></search><sort><creationdate>20220603</creationdate><title>Product recommendation method and device, computer storage medium and system</title><author>DING QIANJIN</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_CN114581165A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>chi ; eng</language><creationdate>2022</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>DING QIANJIN</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>DING QIANJIN</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Product recommendation method and device, computer storage medium and system</title><date>2022-06-03</date><risdate>2022</risdate><abstract>The invention provides a product recommendation method and device, a computer storage medium and a system. The method comprises the following steps: determining a target product potential expected value and a target gradient value of a target user; based on the target product potential expected value and the target gradient value, determining a similar user set; in the similar user set, obtaining a plurality of gradient values of each user corresponding to the plurality of to-be-recommended products, and forming a similar user gradient value set by using the plurality of gradient values; and determining at least one recommendation gradient value in the similar user gradient value set, and recommending at least one to-be-recommended product corresponding to the at least one recommendation gradient value to the target user. Therefore, the change trend of products preferred by the target user can be analyzed through the target product potential expected value and the target gradient value, so that the similar us</abstract><oa>free_for_read</oa></addata></record> |
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| language | chi ; eng |
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| subjects | CALCULATING COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING PHYSICS SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Product recommendation method and device, computer storage medium and system |
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