Entity article recommendation method and device, server and storage medium

A technology for physical items and recommendation methods, applied in the field of servers and storage media, devices, and physical item recommendation methods, can solve problems such as inability to meet accuracy, occupation, and multi-processing resources, and achieve improved accuracy, reduced occupation, and analysis. accurate effect

Inactive Publication Date: 2019-12-20
TENCENT TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the physical items that each user is interested in are not the same, and the recommendation of popular items or newly launched items is not suitable for each user. To obtain a fixed number of users who successfully

Method used

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  • Entity article recommendation method and device, server and storage medium
  • Entity article recommendation method and device, server and storage medium
  • Entity article recommendation method and device, server and storage medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0037] The solution of the present invention can generate the recommendation information of the physical item when the user is operating the computer application, or when the user browses the surrounding physical items of the application, and present the recommendation information to the user, so that the user can pass the physical item The recommendation information obtains relevant recommended physical items, thereby promoting game users' attention or purchase of the physical items, and the generated physical item recommendation information is different for different users, thereby improving the accuracy of the physical item recommendation for different users.

[0038] Among them, in the embodiment of the present invention, the target application may be a web version application or a client application. The corresponding physical items are items that have an association relationship with the target application, such as icon dolls, commemorative coins, and commemorative toys of t...

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Abstract

The invention discloses an entity article recommendation method and device, a server and a storage medium, and belongs to the technical field of artificial intelligence. The entity article recommendation method includes: obtaining user characteristic information of the to-be-recommended user by utilizing the entity article recommendation date; obtaining a to-be-recommended entity article by utilizing the user feature information; and performing entity article screening in the to-be-recommended entity articles by utilizing the attribute information of the entity articles to obtain target entityarticles. The feature information of the user at least comprises the operation information behavior feature information of the user in the target application and the operation behavior feature information of the to-be-recommended user on the entity article; therefore, the analysis of the preference degree of the user to the physical object is more accurate; and screening is carried out in combination with the attribute information of the entity articles, so that the recommended entity articles better meet the requirements of the current recommended user, the occupation of server processing resources in the recommendation process is reduced, and the accuracy of entity article recommendation for different users is improved.

Description

Technical field [0001] The present invention relates to the technical field, in particular to a method, device, server and storage medium for recommending physical items. Background technique [0002] Users are usually more interested in physical items around computer applications. For example, game users are usually interested in physical items around game applications, which will prompt users to purchase corresponding physical items, such as figures and dolls. [0003] In order to be able to recommend physical items to users, the recommending server usually recommends popular physical items or newly listed physical items to users. However, the physical items of interest of each user are not the same, and the recommendation of popular items or newly listed items is not suitable for every user. To obtain a fixed number of users who successfully recommend items, the server needs to frequently recommend item information to users , It will take up too much processing resources, and t...

Claims

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Application Information

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IPC IPC(8): H04N21/25H04N21/258H04N21/478A63F13/52A63F13/822
CPCA63F13/52A63F13/822H04N21/251H04N21/25891H04N21/4781
Inventor 陈航陈易斐
Owner TENCENT TECH (SHENZHEN) CO LTD
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