Character String Matching via Scrubbing and Stemming
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Solution Overview
Problem
Existing systems face challenges in accurately matching and standardizing character strings from seller listings with pre-defined catalogues, particularly in ticket listings, due to inconsistent user terminology and formatting.
Innovation Solution
A system comprising a matching application with a scrubbing application that includes cleaning, stemming, formatting, and alias applications, which processes input strings by removing non-alpha-numeric characters, standardizing spacing, converting abbreviations, reformatting, and checking for aliases to match them with a catalogue database, ensuring consistent comparison.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If user input is accepted in various formats and terminologies, then ease of operation is improved, but matching precision deteriorates
Solution Approach 1:
The system performs preliminary actions by cleaning, standardizing, and normalizing character strings before matching them against the catalogue database. This includes removing non-alphabetic characters, converting to lowercase, and applying stemming algorithms to root words, ensuring that diverse user inputs are pre-processed into a consistent format that improves matching accuracy
Solution Approach 2:
The patent introduces an intermediary processing layer between user input and database matching. This intermediary includes multiple applications (cleaning application, stemming application, formatting application, alias application) that act as mediators to transform varied user inputs into standardized forms that can be accurately matched against the catalogue database
2Measurement precision
If multiple processing applications are applied to standardize input, then matching accuracy is improved, but device complexity increases
Solution Approach 1:
The system segments the complex task of string matching into multiple specialized applications: a cleaning application for removing non-alphabetic characters, a stemming application for reducing words to root forms, a formatting application for standardizing case and spacing, and an alias application for handling alternative terms. Each application performs a specific function, making the overall complex system manageable and maintainable through functional decomposition
3Manufacturing precision
If strict terminology matching is enforced, then manufacturing precision is improved, but ease of operation deteriorates
Solution Approach 1:
The system applies parameter changes by transforming the characteristics of input strings through multiple processing stages: removing non-alphabetic characters, converting to lowercase, applying stemming to reduce words to their root forms, and handling aliases. These parameter transformations enable strict matching precision while maintaining ease of operation by automatically handling the normalization process
Data Source
AI summary
A method for determining whether an entered character string corresponds to terminology utilized in a catalogue database, comprising: accepting the entered character string; determining if the character string matches terminology utilized in the database; if the character string does not match terminology utilized in the database, applying at least one action to the character string to create an edited character string; and determining if the edited character string matches terminology utilized in the database.