Advertising Campaign Content Filtering via Global Standards Models
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Solution Overview
Problem
Existing advertising systems fail to effectively prevent the presentation of objectionable content media with advertising campaigns, leading to inefficient and ineffective advertising due to the lack of a robust mechanism to filter out violating content based on global content standards and advertiser preferences.
Innovation Solution
A method that trains global standards models and campaign characteristic models to identify violating content media, updates advertising scores, and maintains block lists to ensure compliant content is used for advertising campaigns, thereby preventing the presentation of objectionable content and optimizing advertising efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If advertising campaigns are presented without content filtering, then advertising reach and exposure are maximized, but objectionable content may be associated with ads leading to brand damage and reduced advertising effectiveness
Solution Approach 1:
The system performs preliminary content analysis by training global standards models and campaign characteristic models before advertising campaigns are presented. Block lists are pre-generated based on violated global content standards, and advertising scores are pre-calculated based on category scores and advertiser preferences. This preliminary action ensures that only compliant content is associated with ads, preventing brand damage while maintaining advertising effectiveness.
Solution Approach 2:
The patent introduces intermediary components including global standards models, campaign characteristic models, and advertising score mechanisms that mediate between content media and advertising campaigns. These intermediaries evaluate content compliance and determine advertising suitability, resolving the contradiction by filtering objectionable content while allowing legitimate advertising reach.
2Reliability
If a robust content filtering mechanism is implemented, then objectionable content is effectively blocked, but system complexity and processing requirements increase
Solution Approach 1:
The content filtering system is segmented into multiple specialized models: global standards models for general content compliance, campaign characteristic models for ad-specific requirements, and category-based scoring systems. This segmentation allows each component to focus on specific aspects of content evaluation, improving reliability while managing complexity through modular design.
Solution Approach 2:
The system uses parameter-based advertising scores that change based on content category evaluations and advertiser preferences. By transforming content characteristics into quantifiable scores and thresholds, the system manages filtering complexity through parameter optimization rather than complex rule sets.
3Measurement precision
If advertising scores are updated based on category scores and advertiser preferences, then advertising precision and targeting accuracy improve, but processing time and computational resources increase
Solution Approach 1:
Advertising scores are pre-calculated based on category scores and advertiser preferences before campaigns are executed. This preliminary scoring allows for rapid deployment of targeted advertising without real-time computational delays, maintaining precision while reducing processing time during actual campaign delivery.
Solution Approach 2:
The system calculates advertising scores for all content categories comprehensively, even though not all categories may be relevant to every campaign. This excessive action ensures that when a campaign is launched, the targeting accuracy is maximized without needing to recalculate scores in real-time, trading some computational resources for time efficiency.
Data Source
AI summary
For presenting advertising campaigns, a method trains a global standards model with global content standards and/or advertising scores. The method trains a plurality of campaign characteristic models on campaign characteristics and/or the advertising scores. The method identifies whether content media violates the global content standards using the global standards model. In response to the content media violating the global content standards, the method adds the identified content media to a block list. The method updates the advertising score for the content media for each of the plurality of advertising campaigns based on the category scores and advertiser preferences for the plurality of advertising campaigns. The method presents a given advertising campaign for the content media based on the advertising score and the block list.