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A virtual item recommendation method, device, and computer-readable storage medium

A recommendation method and a technology of props, applied in the field of artificial intelligence, can solve the problems of low accuracy and achieve the effect of accurate recommendation and accurate real preference

Active Publication Date: 2022-04-08
TENCENT TECH (SHENZHEN) CO LTD
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0004] During the research and practice of the prior art, the inventors of the present application found that when predicting the user's preference for game props in the prior art, the prediction accuracy rate is low

Method used

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  • A virtual item recommendation method, device, and computer-readable storage medium
  • A virtual item recommendation method, device, and computer-readable storage medium
  • A virtual item recommendation method, device, and computer-readable storage medium

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Embodiment Construction

[0084] It should be noted that artificial intelligence (AI) is a theory, method, and technology that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use knowledge to obtain the best results. and application systems. In other words, artificial intelligence is a comprehensive technique of computer science that attempts to understand the essence of intelligence and produce a new kind of intelligent machine that can respond in a similar way to human intelligence. Artificial intelligence is to study the design principles and implementation methods of various intelligent machines, so that the machines have the functions of perception, calculation and decision-making.

[0085] Artificial intelligence technology is a comprehensive subject that involves a wide range of fields, including both hardware-level technology and software-level technology. Artificial intellig...

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Abstract

The present application discloses a virtual item recommendation method, device, and computer-readable storage medium, wherein, by obtaining a heterogeneous network of a target game; using a heterogeneous network characterization learning model to represent the target user nodes therein as user learning vectors, and Represent each item node as an item learning vector; obtain the first preference information of the target game user for each game virtual item according to the user learning vector and the item learning vector; obtain the historical operation sequence of the target game user, and pass the timing model Characterize the historical operation sequence as a time series learning vector; obtain the second preference information of the target game user for each game virtual item according to the time series learning vector and the item learning vector; Recommend game virtual props. It can more accurately recommend game virtual props to game users.

Description

technical field [0001] The present application relates to the technical field of artificial intelligence, in particular to a virtual item recommendation method, device and computer-readable storage medium. Background technique [0002] With the rapid development of artificial intelligence technology, by deploying intelligent recommendation algorithms on the server, it is possible to make targeted recommendations to users. Taking games as an example, it is possible to recommend game virtual items that users may prefer. [0003] In the existing technology, an intelligent recommendation algorithm based on a graph representation learning model is usually used to learn the user's preference for game items. This intelligent recommendation algorithm represents both the user and the game virtual item as a vector, and finally uses the similarity between the two vectors to To predict the user's preference for a game item. [0004] During the research and practice of the prior art, th...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): A63F13/79
CPCA63F13/79
Inventor 蔡红云程序何峰张发强姚亮
Owner TENCENT TECH (SHENZHEN) CO LTD
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