Live Streaming Recommendation via Social Interaction Data
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Solution Overview
Problem
Users face difficulty in selecting diverse and engaging live streaming rooms due to recommendations often based on statistical data, leading to aesthetic fatigue and limited content variety.
Innovation Solution
A method and apparatus that acquire social information of a user account to select live streaming rooms based on interaction data from associated user accounts, generating recommendation information that highlights popular or interesting rooms among friends, thereby enriching the variety of recommended content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If live streaming rooms are recommended based on statistical data from users' watching history, then the recommendation system is simple to implement, but the diversity and variety of recommended content is limited causing aesthetic fatigue
Solution Approach 1:
The patent combines multiple recommendation dimensions including social interaction data, user watching history, and live streaming room attributes to generate comprehensive recommendation scores. This merging of different data sources enriches the recommendation content variety while maintaining system feasibility through modular implementation.
2Ease of operation
If users access live streaming rooms randomly from home page recommendations, then users have freedom of choice, but the success rate of accessing interesting rooms decreases due to difficulty in accurate selection
Solution Approach 1:
The patent implements feedback mechanisms by analyzing user interaction data including watching history, interaction behavior, and social relationship data to continuously optimize recommendation accuracy. This feedback loop enables the system to learn from user behavior and improve the reliability of recommendations while preserving user autonomy in selection.
3Productivity
If recommendation information includes social relationship data showing which friends are watching, then user engagement and interest increase, but the amount of data processing and analysis required increases
Solution Approach 1:
The patent extracts and utilizes specific social relationship features such as friend watching status and interaction history to enhance recommendation effectiveness. By selectively extracting relevant social data rather than processing all possible social information, the system improves user engagement while controlling data processing complexity through focused feature selection.
Data Source
AI summary
The disclosure provides a method and an apparatus for recommending a live streaming room, and a storage medium. The method is implemented as follows. Social information of a target user account is acquired in response to detecting a predetermined operation from the target user account. A target live streaming room is selected based on interaction data of each associated user account indicated by the social information. Information on the target live streaming room is displayed to the target user account.