Automated Content Customization via Social Graph Mapping

Solution Overview

Problem

Personalizing digital content, such as audiobooks, is time-consuming and inefficient, requiring extensive re-recording of narration to replace character names and references, making it costly and impractical for individual customization.

Innovation Solution

A computer-implemented content processing service that utilizes social graphs and supplemental graphs to automatically replace character names and attributes in digital content with user-specific information, allowing for efficient customization of text, audio, and multimedia content by identifying and mapping objects, attributes, and relationships within the content and user-provided social data.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If a narrator re-records narration to personalize digital content for different users, then the content can be customized to suit individual user interests and relationships, but the process becomes time-consuming and costly

Engineering Contradiction:

Improvecontent personalizationVSAvoidnarration re-recording time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system creates a personalized copy of the original content by automatically substituting character names and relationships with user-specific information from social graphs. Instead of re-recording the entire narration, the system generates a customized version by replacing specific elements (character names, relationships) while maintaining the original narration structure and audio recording.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system pre-processes the original content by identifying and tagging character names, relationships, and other customizable elements before personalization is needed. Social graphs are pre-built and stored, containing user information and relationships that can be quickly mapped to content elements during the personalization process, eliminating the need for time-consuming manual customization when a user requests personalized content.

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If a narrator re-records narration to personalize digital content for different users, then the content can be customized to suit individual user interests and relationships, but the process becomes expensive and inefficient

Engineering Contradiction:

Improvecontent personalizationVSAvoidcustomization efficiency

Core Design Contradiction:

Adaptability or versatilityVSProductivity

Solution Approach 1:

The system creates a personalized copy of the original content by automatically substituting character names and relationships with user-specific information from social graphs. Instead of re-recording the entire narration, the system generates a customized version by replacing specific elements (character names, relationships) while maintaining the original narration structure and audio recording.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The system automates the personalization process using algorithms that automatically map user social graph data to content elements. The system independently performs name substitutions, relationship mappings, and content generation without requiring manual narrator intervention for each customization request, thereby dramatically improving productivity and reducing costs.

Inventive Principle:

Principle #25Self-service

3Manufacturing precision

If multiple character mapping options are considered for personalization, then the content can be more accurately tailored to user preferences, but the complexity of the customization process increases

Engineering Contradiction:

Improvecharacter mapping accuracyVSAvoidcustomization process complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system presents multiple character mapping options to the user and receives feedback on their preferences. Based on this feedback, the system learns and refines its mapping decisions, automatically selecting the most appropriate character mappings for future personalizations. This feedback mechanism enables the system to achieve high mapping accuracy while maintaining process efficiency, as the complexity of evaluating multiple options is reduced through iterative learning.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS9037956B2Content customization

Publication Date: 2015.05.19 AUDIBLE INC

AI summary

A content processing service may analyze an item of original content and identify several objects, attributes of those objects, and relationships between those objects present in the item of original content. The content processing service may also analyze a source graph, such as a social graph or supplemental graph, and identify several objects, attributes of those objects, and relationships between those objects present in the source graph. The content processing service may customize the item of original content by selecting an original object and selecting a source graph object. One or more of the attributes or relationships of the selected original object in the item of original content may be replaced by one or more of the attributes or relationships of the selected source graph object, thereby forming an item of modified content.