Personalized Playlist Generation via Latent Factor Matching

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Solution Overview

Problem

Existing music-streaming applications fail to seamlessly integrate playlist management features with personalized media recommendations, leading to an incompatible and disjointed user experience.

Innovation Solution

A system and method for periodically generating personalized playlists based on a user's recent taste profile, using latent factor vectors to match user preferences with media attributes, allowing for batched recommendations that can be manipulated and used for offline listening, and improving future recommendations based on user interaction.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If music recommendations are provided through curated radio stations with initial user input, then personalized music suggestions can be generated, but playlist management features (sharing, following, offline listening) become incompatible or disjointed from the recommendation experience

Engineering Contradiction:

Improveplaylist management integrationVSAvoiduser experience compatibility

Core Design Contradiction:

Adaptability or versatilityVSEase of operation

Solution Approach 1:

The patent merges the radio station recommendation experience with playlist management features by allowing users to convert radio stations into playlists and enabling all standard playlist operations (sharing, following, offline listening) within the same interface, eliminating the disconnect between recommendations and playlist features

Inventive Principle:

Principle #5Merging (Combining)

2Measurement precision

If collaborative filtering methods are used to predict user preferences from many users' data, then music recommendation accuracy improves, but the system cannot incorporate normal on-demand music selection activities (searching, favoriting, playlist management)

Engineering Contradiction:

Improvepreference prediction accuracyVSAvoidactivity data integration

Core Design Contradiction:

Measurement precisionVSAdaptability or versatility

Solution Approach 1:

The patent creates a unified system that handles multiple types of user activities (searching, favoriting, playlist management, radio station interaction) through a single recommendation engine that generates both radio stations and playlists, allowing all activity types to contribute to preference prediction accuracy

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS10872110B2Systems, apparatuses, methods and computer-readable medium for automatically generating playlists based on taste profiles

Publication Date: 2020.12.22 SPOTIFY

AI summary

Methods, systems and computer program products for periodically generating a personalized playlist of media objects based on a most recent taste profile of a user. An N-dimensional latent factor vector that defines a taste profile of a user is constructed and matched to an M-dimensional latent factor vector that defines attributes of a media object. A playlist including the first media object is generated based on the matching.