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Game commodity recommendation method and device and electronic equipment

A product recommendation and game technology, applied in the computer field, can solve problems such as high deviation of user preference prediction results and poor user experience, and achieve the effect of improving experience

Pending Publication Date: 2021-03-05
广州三七互娱科技有限公司
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Problems solved by technology

However, in practical applications, since the clustering method is based on the distance between two data, and there is no upper limit for the preference degree value during preference prediction, when the number of users is large and the payment characteristics of a certain user are high When , the preference prediction after the overall clustering will only show two polar results, which makes the deviation of the user preference prediction result higher, so that the game products recommended to the user do not match the actual situation of the user, which leads to poor user experience

Method used

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  • Game commodity recommendation method and device and electronic equipment
  • Game commodity recommendation method and device and electronic equipment
  • Game commodity recommendation method and device and electronic equipment

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Embodiment Construction

[0056] This part will describe the specific embodiment of the application in detail. The preferred embodiment of the application is shown in the accompanying drawings. Each technical feature and overall technical solution of the application, but it should not be understood as a limitation on the protection scope of the application.

[0057] Currently, the user's preference prediction is clustered by obtaining the user's payment characteristics, and the user's preference for a certain type of commodity is predicted according to the clustering result, so that corresponding virtual items are recommended according to the predicted preference. However, in practical applications, since the clustering method is based on the distance between two data, and there is no upper limit for the preference degree value during preference prediction, when the number of users is large and the payment characteristics of a certain user are high When , the preference prediction after the overall clu...

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Abstract

The invention discloses a game commodity recommendation method and device, and electronic equipment. The method comprises the steps of obtaining payment feature data of a user; performing logarithm normalization processing on the payment feature data to obtain a feature probability value of the payment feature data; and determining a preference label corresponding to the payment feature data according to an interval section where the feature probability value is located in a preset interval, so as to send corresponding commodity recommendation information to the user according to the preference label.

Description

technical field [0001] The present application relates to the field of computer technology, in particular to a game product recommendation method, device and electronic equipment. Background technique [0002] With the development of the Internet, the services that can be recommended to users are gradually increasing. In order to meet user needs, in some fields, such as games, it is usually necessary to formulate corresponding services based on user product preferences to meet user needs. Therefore, it is necessary to predict user product preferences to provide users with different preferences Recommend corresponding virtual items to improve user experience. [0003] Currently, the user's preference prediction is clustered by obtaining the user's payment characteristics, and the user's preference for a certain type of commodity is predicted according to the clustering result, so that corresponding virtual items are recommended according to the predicted preference. However...

Claims

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Application Information

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IPC IPC(8): G06Q30/06A63F13/792
CPCG06Q30/0631A63F13/792A63F2300/575
Inventor 刘舟徐键滨吴梓辉徐雅王理平
Owner 广州三七互娱科技有限公司
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