Dynamic Rules Engine for Client-Side Content Categorization
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Solution Overview
Problem
Publishers face challenges in understanding audience behavior patterns due to the lack of standardization in content categorization across various content delivery systems, with existing automated solutions being expensive and unable to detect nuances that humans can identify.
Innovation Solution
A system and method using a universal data agent with a dynamic rules engine that categorizes content on client devices, allowing for the determination of content categories and segments for targeted advertising, by transmitting rules to the client device for evaluation with the rules engine.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If text mining and automated techniques are used to categorize content, then content categorization can be performed, but the solution becomes expensive and complex software that publishers cannot adequately maintain
Solution Approach 1:
The patent extracts the content categorization logic from complex centralized software systems and implements it through simple, lightweight rules that can be directly embedded in or transmitted to client devices. This allows publishers to perform automated categorization without requiring expensive, complex maintenance infrastructure.
Solution Approach 2:
The patent uses simple, easily replaceable rules rather than complex permanent software systems. These rules can be transmitted to client devices and updated as needed, providing a cost-effective solution that avoids the need for expensive, long-term software maintenance contracts.
2Extent of automation
If text mining and automated techniques are used to categorize content, then content categorization can be performed, but such solutions miss nuances that humans readily detect
Solution Approach 1:
The patent employs dynamic rules that can adapt to different content contexts and nuances. The rules engine evaluates content against multiple criteria and can adjust its categorization based on the specific characteristics of the content, allowing it to capture human-like nuances while maintaining automation.
Solution Approach 2:
The system changes the parameters used for evaluation by allowing rules to consider multiple dimensions of content characteristics. This enables the automated system to adjust its assessment criteria based on the specific content being analyzed, improving accuracy to match human judgment.
3Measurement precision
If publishers manually categorize content, then nuanced understanding is achieved, but this does not scale with the explosion of information across the Internet
Solution Approach 1:
The patent enables client devices to autonomously perform content categorization using embedded rules engines. This self-service approach eliminates the need for manual categorization by human publishers while maintaining high accuracy, allowing the system to scale automatically with the volume of content.
Solution Approach 2:
The patent accelerates the categorization process by using efficient rule evaluation mechanisms that can quickly assess content against multiple criteria. This accelerated automated processing enables high throughput while maintaining the nuanced accuracy that would otherwise require slow manual review.
4Stability of the object's composition
If centralized content categorization systems are used, then standardization can be enforced, but the system becomes expensive and complex to maintain
Solution Approach 1:
The patent segments the categorization function into distributed components, with simple rules deployed to individual client devices rather than requiring a complex centralized system. This segmentation maintains standardization through consistent rule application while dramatically reducing overall system complexity and maintenance requirements.
Data Source
AI summary
A system and method for determining client metadata using a dynamic rules engine is disclosed. The system may include a universal data agent, a site management tool, a targeting engine, an ad server, and a data warehouse. When a visitor visits a site on a content delivery system, the universal data agent and targeting engine may collect data about the visitor and site. The site management tool may configure the universal data agent and provided current rules for the dynamic rules engine. The collected data may be stored in the data warehouse and evaluated in the dynamic rules engine to produce a content category. The ad server may use the content category to serve targeted ads and/or other content to the visitor.