Group Playlist Generation via Taste Profile Vector Aggregation
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Solution Overview
Problem
Existing media distribution platforms do not allow multiple users to contribute to a single playlist, resulting in limited user involvement in media content selection during group settings.
Innovation Solution
A method and system for generating a group playlist by identifying user taste profiles, creating a group taste profile, selecting candidate media content items based on individual and group preferences, and ranking these items to create a playlist that suits the collective taste of the group.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single user controls playlist creation, then the playlist can be easily managed and played, but other users in the group have no involvement in media content selection
Solution Approach 1:
The patent merges multiple individual user taste profiles into a single group taste profile through vector space aggregation. Each user's taste profile is represented as a vector, and these vectors are combined to create a composite group taste profile that captures collective preferences, enabling both easy playlist management and meaningful user involvement simultaneously
Solution Approach 2:
The patent introduces a taste profile vector as an intermediary representation that mediates between individual user preferences and group playlist selection. This vector space model translates complex user preferences into a unified structure that can be used for automated playlist generation while reflecting individual user contributions
2Adaptability or versatility
If the system analyzes individual user taste profiles and generates personalized recommendations, then user engagement increases, but the system complexity increases
Solution Approach 1:
The patent transforms complex user preference data into simplified vector representations in a multi-dimensional space. By converting taste profiles into vectors with specific dimensions representing different content characteristics, the system reduces complexity while maintaining the ability to analyze individual preferences and generate personalized recommendations
Solution Approach 2:
The patent moves from analyzing individual user profiles in a complex high-dimensional space to representing group preferences through a single aggregated vector. This dimensional transformation simplifies the computation required for playlist generation while preserving the richness of individual user taste information through the vector space model
Data Source
AI summary
Methods, systems, and computer programs for generating a playlist of media content items for a group of users. Media content items listened to by the selected users are compared to an average user taste profile to select media content items for playback to the group of users.