Weighted Keyword Matching for Lost and Found Records
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Solution Overview
Problem
Current systems for locating and merging lost and found records require manual comparison of data fields, which is inefficient and prone to errors, especially when dealing with forgotten items in various settings like hotels or rental cars.
Innovation Solution
A system and method that utilize weighted keywords to match and merge data fields in lost and found records, displaying potential matches based on a high weighted percentage of use, allowing for automatic comparison and presentation of differences in merged records.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual comparison of data fields is used to match lost and found records, then the process is simple to implement, but it is inefficient and prone to errors
Solution Approach 1:
The patent replaces the manual mechanical comparison process with an automated computer-based system that uses keyword matching algorithms and weighted scoring to automatically identify and match lost and found records, thereby improving both efficiency and accuracy
Solution Approach 2:
The system enables self-service matching by automatically comparing record data fields, generating match scores, and presenting potential matches without requiring manual intervention, allowing the system to serve itself in the matching process
2Measurement precision
If automated keyword matching with weighted percentages is implemented, then matching accuracy improves, but system complexity increases
Solution Approach 1:
The patent changes the parameter of match determination by introducing weighted keywords and percentage thresholds, transforming the matching process from simple equality checking to a nuanced scoring system that considers multiple factors with different importance weights
Solution Approach 2:
The system segments the matching process into distinct components: keyword identification, weight assignment, score calculation, and threshold comparison, making the complex automated matching process more manageable and understandable
3Measurement precision
If all data fields are compared in detail, then matching precision improves, but processing time increases
Solution Approach 1:
The patent extracts and prioritizes key identifying keywords from full data fields, focusing the matching process on these critical elements first, and only performing detailed comparison on remaining fields when initial keyword matching indicates potential matches
Solution Approach 2:
The system performs preliminary keyword matching and scoring before conducting detailed field-by-field comparison, filtering out obviously non-matching records early in the process to reduce the amount of time spent on comprehensive analysis
Data Source
AI summary
In one embodiment, a system, method, and apparatus to generate a merged record comprises a client server configured to generate a first report; and a recovery server configured to: receive the first report, the first report including first report information including at least one first descriptive term and a customer ID; match the at least one first descriptive term to one of a plurality of descriptive terms in a descriptive term list; determine if a weighted percentage associated with the matched at least one first descriptive term is greater than a predetermined weighted percent; match the at least one first descriptive term to at least one second descriptive term in at least one second report if it is determined that the weighted percentage associated with the matched at least one first descriptive term is greater than the predetermined weighted percent.