Automated Customized Media Creation via Rule Engine
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Solution Overview
Problem
Current systems for creating customized digital media lack the ability to incorporate additional parameters effectively, limiting the generation of personalized content beyond basic metadata associations.
Innovation Solution
A method for automating the creation of customized media by generating media content, reviewing associated metadata, and applying sets of rules to produce a customized output, which can include generating scripts for various media formats such as websites, books, and dynamic storybooks, using a system comprising a web server, media content store, and business rules engine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If basic metadata association is used to create customized media, then the media can be personalized with minimal processing, but the customization depth and richness are limited
Solution Approach 1:
The patent segments the customization process into distinct modules: metadata extraction module, rule engine module, and media generation module. Each module handles specific tasks independently, allowing the system to achieve deep customization capabilities while maintaining manageable complexity through modular architecture. The rule engine is further segmented into multiple rule sets that can be applied independently to different aspects of media customization.
Solution Approach 2:
The system employs a universal rule engine that can process multiple types of metadata (EXIF, IPTC, XMP) and apply various rule sets to different media formats (images, videos, audio). This multi-functional approach allows a single system to handle diverse customization requirements without requiring separate specialized systems for each media type or metadata format.
2Adaptability or versatility
If multiple parameters and rule sets are applied to generate customized media, then richly tailored content can be created, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and validating metadata during ingestion, organizing it into standardized structures. Rule sets are pre-compiled and cached for efficient execution. This preliminary preparation reduces the computational burden during actual media generation, allowing rich customization without excessive processing delays when users request customized media outputs.
Solution Approach 2:
The rule engine implements partial action by allowing users to select specific rule sets applicable to their needs rather than applying all possible rules. This selective application of rules enables rich customization where needed while avoiding unnecessary processing of irrelevant rules, thereby reducing overall processing time while maintaining customization richness for the selected parameters.
3Extent of automation
If automated rule-based systems are used to create customized media, then manual intervention is reduced, but the flexibility to handle complex customization scenarios decreases
Solution Approach 1:
The rule engine is designed as a dynamic system that can adapt its behavior based on the input metadata and user preferences. Rules can be enabled or disabled dynamically, and the engine can adjust its processing strategy based on the complexity of the customization scenario. This dynamic nature allows the system to maintain high automation levels while flexibly handling complex scenarios by activating appropriate rule combinations as needed.
Solution Approach 2:
The system incorporates feedback mechanisms where the results of rule applications are evaluated and can trigger additional rule sets or adjustments. This feedback loop allows the automated system to handle complex customization scenarios by iteratively applying rules and adjusting based on intermediate results, maintaining high automation while achieving the flexibility needed for complex media customization requirements.
Data Source
AI summary
A system and method for automating the creation of customized media includes generating media content comprising first metadata associated with the media content, reviewing the media content and the first metadata, applying at least one set of rules to the media content and the first metadata, and generating a customized media output based on the media content, the first metadata and the at least one set of rules.