Bayesian Web Search Result Matching System
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Solution Overview
Problem
Manual matching of web content from multiple websites is prone to human error and is time-consuming, as it requires comparing search results across various platforms to identify matching items, which is inefficient and often results in incorrect identifications.
Innovation Solution
An automated system using Bayes theorem to calculate the probability that search results from different websites correspond to the same item, allowing for accurate matching and aggregation of search results without the need for manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual matching process is used to compare search results from multiple websites, then the matching can be performed with human judgment and flexibility, but human error causes mistakes in matching and the process is time-consuming
Solution Approach 1:
The patent replaces the manual mechanical matching process with an automated computer-based system that uses algorithms to compare search results. The system automatically extracts attributes from search results, compares them using predefined criteria, and determines matches without human intervention, thereby eliminating human error and significantly reducing matching time.
Solution Approach 2:
The system enables self-service matching where the computer automatically performs the entire matching process without requiring human operators. The automated system extracts, compares, and matches search results independently, making the process both faster and more reliable by removing human factors from the equation.
2Productivity
If manual matching process is used to identify matching items across websites, then human engineers can handle complex cases, but the process requires significant human effort and is inefficient for large volumes of search results
Solution Approach 1:
The patent replaces manual human operations with an automated computer-based matching system that can process large volumes of search results efficiently. The system handles attribute extraction, comparison, and matching automatically, dramatically increasing productivity while maintaining operational simplicity through automated workflows.
3Productivity
If automated matching system is implemented to eliminate manual processes, then human error is reduced and efficiency increases, but the system complexity increases
Solution Approach 1:
The patent segments the matching process into distinct automated components: attribute extraction, attribute comparison, and match determination. Each component handles a specific aspect of the matching process, making the overall system more manageable and maintainable while achieving high productivity through automation.
Data Source
AI summary
Provided are a system and method for matching search results from multiple websites. In one example, the method includes calculating a probability that a search result of a first website corresponds to a same item as a search result of a second website based on Bayes theorem, in response to the calculated probability being greater than a predetermined threshold, determining that the search result of the first website and the search result of the second website are a match, and displaying an aggregated list of search results combined from the first website and the second website based on the matched search results. By auto-matching search results using Bayes theorem, a true match can be determined that is more accurate in comparison to a manual matching operation performed by a human.