Shared Playback Queue Personalization by Content Source Attribution
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Solution Overview
Problem
Existing media content systems struggle to personalize content during shared media playback sessions, as they fail to distinguish between media items selected by the user and those selected by others, leading to uncontrolled influence on the user's listening history and recommendations.
Innovation Solution
A method and system that identifies the source of media content items in a shared playback queue, determining whether to include them in the user's listening history and providing personalized recommendations based on this distinction, thereby reducing user input and processing requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If all media items in a shared playback queue are included in the user's listening history, then the listening history becomes comprehensive, but the personalization accuracy deteriorates because items selected by others are mixed with items selected by the user
Solution Approach 1:
The listening history is segmented into two distinct components: items selected by the user and items selected by others in the shared session. This segmentation allows the system to maintain a complete record of all consumed media while simultaneously enabling precise personalization by distinguishing between user-driven and others-driven selections. The patent implements this by tracking the source of each media item addition to the queue, thereby separating the listening history into user-specific and shared-session portions.
2Loss of information
If the system tracks and processes all user data from shared sessions, then comprehensive user preferences are captured, but the data processing complexity increases
Solution Approach 1:
The patent extracts and isolates only the critical data element needed for personalization: the identity of the media item selector. Instead of processing and storing all user interaction data from shared sessions, the system extracts merely the source attribution information (who added the item to the queue). This extraction approach captures comprehensive preference data while minimizing processing complexity by focusing only on the essential attribution signal.
3Adaptability or versatility
If personalized recommendations are generated from all listened content in shared sessions, then recommendation coverage is improved, but the personalization quality deteriorates due to mixed selection sources
Solution Approach 1:
The patent applies local quality by generating different types of recommendations based on the source of media consumption. For items selected by the user, the system generates highly personalized recommendations reflecting their specific tastes. For items selected by others, the system either excludes them from personalization calculations or generates separate recommendation streams. This local differentiation ensures that recommendation quality is optimized for user-driven content while maintaining broad coverage through inclusion of all consumed content in the analysis pool.
Data Source
AI summary
An electronic device receives a request, from a host user, to initiate a shared playback session. The electronic devices streams media from a playback queue for the shared playback session to the first device and to additional devices. The electronic device determines that the host user has left the shared playback session, and, in response, maintains the playback queue to be accessed by the additional devices. After the host user has left the shared playback session, the electronic device provides media from the playback queue to at least a second device of the additional devices. While providing the media the playback queue, the electronic device receives a request, from the second device, to leave the playback queue and, in response, provides a second media, that is not included in the playback queue, to the second device. The electronic device ceases to provide the playback queue to the second device.