18516730. DIGITAL AVATAR RECOMMENDATION METHOD AND RECOMMENDATION SYSTEM simplified abstract (Alipay (Hangzhou) Information Technology Co., Ltd.)

DIGITAL AVATAR RECOMMENDATION METHOD AND RECOMMENDATION SYSTEM

Organization Name

Alipay (Hangzhou) Information Technology Co., Ltd.

Inventor(s)

Junwu Xiong of Hangzhou (CN)

Xiaoyu Tan of Hangzhou (CN)

Hairui Xu of Hangzhou (CN)

James Zhang of Hangzhou (CN)

Wei Chu of Hangzhou (CN)

Yunzhou Shi of George Town (KY)

Zhongzhou Zhao of George Town (KY)

Wei Zhou of George Town (KY)

Xiaolong Li of George Town (KY)

DIGITAL AVATAR RECOMMENDATION METHOD AND RECOMMENDATION SYSTEM - A simplified explanation of the abstract

This abstract first appeared for US patent application 18516730 titled 'DIGITAL AVATAR RECOMMENDATION METHOD AND RECOMMENDATION SYSTEM

Simplified Explanation

The present specification describes a digital avatar recommendation method and system, where a computer-simulated digital avatar interacts with a user to provide personalized content recommendations based on user data and interaction history.

• Obtaining current state data: This step involves collecting user information, scenario information, and interaction history between the user and the digital avatar.
• Mapping state data to target actions: The digital avatar uses reinforcement learning to map the collected data to a target action in a candidate action set, which corresponds to a recommended content category.
• Performing target interaction: The digital avatar then interacts with the user based on the mapped target action, recommending the target content category to the user.

Potential Applications

The technology can be applied in personalized content recommendation systems, virtual assistants, and interactive gaming platforms.

Problems Solved

This technology addresses the challenge of providing individualized recommendations to users based on their preferences and interaction history.

Benefits

Users can receive tailored content recommendations, leading to a more personalized and engaging experience. Content providers can improve user engagement and satisfaction by offering relevant recommendations.

Potential Commercial Applications

This technology can be utilized in e-commerce platforms, streaming services, social media platforms, and online gaming websites to enhance user experience and increase user retention.

Possible Prior Art

One potential prior art could be recommendation systems based on collaborative filtering or content-based filtering methods, which may not provide as personalized recommendations as the digital avatar recommendation method described in this specification.

Unanswered Questions

1. How does the digital avatar adapt to changing user preferences over time? 2. What are the privacy implications of collecting and using user data for personalized recommendations?

Original Abstract Submitted

Implementations of the present specification provide a digital avatar recommendation method and recommendation system. The digital avatar recommendation system includes a computer-simulated digital avatar, and the corresponding recommendation method includes: obtaining current state data, where the state data includes user information of a target user, scenario information of a current scenario, and history information of an interaction between the target user and the digital avatar; mapping, by an agent in the digital avatar, the state data to a target action in a candidate action set based on a current policy obtained through reinforcement learning, where a candidate action in the candidate action set corresponds to a to-be-recommended content category, and the target action corresponds to a target content category; and performing, by the digital avatar, target interaction with the target user, where the target interaction is used to recommend the target content category. As such, individualized recommendation is provided for the target user by using the digital avatar.