Automated Website Policy Compliance Review System
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for ensuring Website quality in advertising networks are inefficient due to the manual review process, which cannot keep pace with the rapid growth of online advertising and often only addresses complaints from advertisers and end users, leaving a need for a more proactive approach to assess policy compliance and quality.
Innovation Solution
An automated system that reviews Websites for policy compliance and quality scoring, allowing for the approval or rejection of Websites before they join an advertising network, and periodic reassessments to maintain quality standards, using a combination of automated checks and manual reviews.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual review of Websites is used to ensure quality compliance, then quality control accuracy is improved, but processing speed and productivity deteriorate
Solution Approach 1:
The review process is divided into two distinct segments: automated preliminary review handling routine compliance checks, and manual expert review reserved for complex or flagged cases. This segmentation allows the system to maintain high accuracy through human expertise while achieving high throughput via automated processing of standard cases.
Solution Approach 2:
An automated review system acts as an intermediary between Website submissions and human experts. This intermediary performs initial filtering, scoring, and flagging of potential issues, preparing cases for manual review and reducing the burden on human reviewers to handle only the most complex cases.
2Productivity
If automated review system is implemented, then processing speed and productivity are improved, but review accuracy and reliability deteriorate
Solution Approach 1:
The system incorporates feedback loops where automated review results are continuously refined based on manual review outcomes and expert corrections. This feedback mechanism allows the automated system to learn from human expertise and improve its accuracy over time while maintaining high processing speeds.
Solution Approach 2:
The automated system serves as an intermediary that prepares cases for manual review, ensuring that human experts focus on complex or ambiguous cases. This intermediary role allows automated processing to handle routine cases at high speed while maintaining overall reliability through selective human intervention.
3Reliability
If comprehensive automated checks are performed, then quality assurance coverage is improved, but system complexity increases
Solution Approach 1:
The comprehensive review process is segmented into multiple independent check modules, each focusing on specific quality aspects such as content policy compliance, technical performance, and user experience metrics. This modular segmentation achieves comprehensive coverage while keeping individual components manageable and maintainable.
4Productivity
If manual review is limited to complaint-based cases, then resource efficiency is improved, but proactive quality control deteriorates
Solution Approach 1:
The system performs preliminary automated reviews of all Website submissions before they go live, proactively identifying and addressing potential quality issues before they become complaints. This preliminary action maintains resource efficiency by automating the screening process while ensuring proactive quality control through comprehensive pre-approval checks.
Data Source
AI summary
The way in which Websites are reviewed for use in an advertising network may be improved by (a) accepting a collection including one or more documents, (b) determining whether or not the collection complies with policies of an advertising network, and (c) approving the collection if it was determined that the collection complies with the policies. The collection may be added to the advertising network if the collection is approved such that (e.g., content-targeted) advertisements may be served in association with renderings of documents included in the collection. The collection may be a Website including one or more Webpages. The policy may concern (A) content of the one or more documents of the collection, (B) usability of a Website wherein the collection of one or more documents is a Website including one or more Webpages, and/or (C) a possible fraud or deception on the advertising network or participants of the advertising network by the collection.