Adaptive Playlist Generation via Contextual Media Interleaving

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Solution Overview

Problem

Users of media players, especially in vehicle-based systems, face frustration due to outdated playlists that require frequent creation or updating, which is time-consuming and inconvenient, especially when the user is occupied while driving.

Innovation Solution

A system and method for generating an adaptive playlist on a vehicle computing device that includes a media player program with modules for storing media items, user preferences, and contextual data aggregation, using a playlist generation engine and contextual media selection engine to create and update playlists based on dynamic vehicle data, such as location, weather, and user history, without user intervention.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If users manually create and update playlists, then playlist content can be customized to user preferences, but it requires frequent user intervention which is time-consuming and inconvenient

Engineering Contradiction:

Improveplaylist customizationVSAvoidtime for playlist creation

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system automatically generates and updates playlists by analyzing user listening history, preferences, and contextual data without requiring manual user input. The playlist generation engine autonomously selects and interleaves media items based on predefined criteria and user profile data, eliminating the need for users to manually create or update playlists while still providing customized content.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system pre-processes user listening history, preferences, and contextual data to generate playlists in advance. By analyzing past behavior patterns and pre-configuring selection criteria, the system prepares customized playlists before the user needs them, so that when playback is requested, the playlist is already optimized according to user preferences and current context.

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If users manually update playlists, then playlist content remains relevant to current preferences, but it becomes increasingly outdated over time requiring frequent recreation

Engineering Contradiction:

Improveplaylist relevanceVSAvoidplaylist validity period

Core Design Contradiction:

Adaptability or versatilityVSDuration of action of stationary object

Solution Approach 1:

The playlist generation engine dynamically creates and updates playlists based on real-time or near-real-time changes in user listening behavior, preferences, and contextual conditions. Rather than using static pre-created playlists, the system continuously adapts playlist content by analyzing new listening patterns and contextual data, ensuring the playlist remains relevant and up-to-date without requiring manual intervention.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system incorporates feedback loops where listening history and user interactions are continuously analyzed to refine and update playlist recommendations. By monitoring actual user behavior patterns and preferences over time, the system receives feedback that enables automatic adjustment of playlist content, ensuring it evolves to match changing user tastes and contextual conditions.

Inventive Principle:

Principle #23Feedback

3Extent of automation

If the system automatically generates playlists, then user intervention is minimized, but the system complexity increases with multiple modules and data processing requirements

Engineering Contradiction:

Improveplaylist generation automationVSAvoidsystem structure

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The playlist generation system is divided into distinct functional modules: a media item selection module that filters and selects candidate media based on user preferences and contextual data, and a playlist generation module that assembles the final playlist by interleaving selected items. This segmentation allows each module to perform its specific function independently, making the overall complex system more manageable and easier to implement through modular components.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The playlist generation engine is designed as a multi-functional system that handles multiple tasks: analyzing user listening history, processing contextual data, selecting media items, and assembling playlists. By consolidating these functions into a single integrated engine rather than separate systems, the patent reduces overall system complexity while maintaining high automation capability.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS8655464B2Adaptive playlist onboard a vehicle

Publication Date: 2014.02.18 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

Systems and methods for generating an adaptive playlist on a computing device onboard a vehicle are provided. The system may include an onboard vehicle computing device configured to execute a media player program. The media player program may include a media storage module configured to store a plurality of media items, a user preference module having user media preferences, a contextual data module configured to receive dynamic contextual data from an onboard vehicle data source, and a playlist manager module. The playlist manager module may include a playlist generation engine configured to generate an adaptive playlist including user playlist media items, and a contextual media selection engine configured to select contextual media items based on the dynamic contextual data and interleave the selected contextual media items into the adaptive playlist.