Search Engine Ranking Adjustment for Fraud Deterrence
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Solution Overview
Problem
Current search engine fraud detection methods are ineffective in preventing fraudulent resources from being listed in search results, as they only identify fraudulent resources after users have interacted with them, failing to deter fraudulent operators effectively.
Innovation Solution
A method and server system that artificially varies user traffic to commercial resources by promoting and demoting them in search results across different time intervals, using randomly-selected values to increase the gap in user traffic, thereby discouraging fraudulent operators by reducing the benefits of their schemes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional fraud detection methods are used to identify fraudulent resources, then fraudulent resources can be detected after user interaction, but the detection occurs too late to prevent fraud and does not effectively deter fraudulent operators
Solution Approach 1:
The patent applies preliminary action by implementing a ranking adjustment mechanism that proactively modifies search result rankings before fraudulent activities can fully exploit the system. The server automatically adjusts rankings based on detected fraud patterns, preventing fraudulent resources from gaining maximum visibility and user interaction, thereby addressing fraud proactively rather than reactively
Solution Approach 2:
The patent implements feedback by creating a closed-loop system where user interactions with search results are continuously monitored, analyzed for fraudulent patterns, and fed back into the ranking adjustment mechanism. This real-time feedback loop enables the system to dynamically respond to fraudulent activities, adjusting rankings based on emerging fraud patterns to maintain detection effectiveness
2Adaptability or versatility
If fraudulent resources are allowed to appear in search results to maintain result completeness, then all relevant resources are provided, but fraudulent operators benefit from continued user traffic
Solution Approach 1:
The patent applies local quality by implementing differentiated treatment for different resources in the search results. Rather than uniformly excluding or including all resources, the system applies specific ranking adjustments to individual fraudulent resources while maintaining normal rankings for legitimate resources. This localized approach preserves search result completeness for valid content while selectively reducing visibility of fraudulent content
Solution Approach 2:
The patent converts the harm of fraudulent resource visibility into benefit by using the presence of fraudulent resources as detection opportunities. The monitoring and analysis of user interactions with search results transforms potentially harmful traffic into valuable data for identifying fraud patterns, which then triggers ranking adjustments that reduce fraudulent visibility while maintaining system security
Data Source
AI summary
A method of and server for ranking documents in response to a query are provided. The method includes determining a target resource hosting a document, and generating a first and a second randomly-selected value for the document. During a first time interval, the method includes acquiring a query and generating a first ranked list of documents to the query based on the first randomly-selected value. The first ranked list includes the document at a promoted-rank position. During the second time interval, the method includes acquiring a query and generating a second ranked list of documents to the query based on the second randomly-selected value. The second ranked list includes the document at a demoted-rank position. The promoted-rank position in the first ranked list is above the demoted-rank position in the second ranked list for increasing a gap in user traffic to the document between the first and second time intervals.