Address Evaluation Platform for Resolving Input Ambiguity
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Solution Overview
Problem
Existing digital systems face challenges in accurately processing address information due to typographical errors and ambiguity, leading to inefficiencies in identifying physical locations, especially when users enter addresses in free-form text without clear parsing mechanisms.
Innovation Solution
A system that uses an address evaluation platform to parse user-input address information, generate candidate addresses based on a database match, and assign quality scores to rank potential addresses, allowing users to select accurate addresses through mobile devices or customer support systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If free-form text address input is allowed, then ease of operation is improved, but measurement precision of address information deteriorates due to typographical errors and ambiguity
Solution Approach 1:
The patent introduces an address evaluation platform as an intermediary between the user's free-form address input and the final address identification. This platform parses the input, generates candidate addresses from a database, evaluates their quality using multiple attributes (string similarity, position accuracy, completeness), and presents ranked results. The intermediary handles the complexity of error correction and disambiguation while allowing users to input addresses casually.
Solution Approach 2:
The system implements feedback by providing users with a ranked list of candidate addresses based on quality scores, allowing them to review and select the correct address. The system also provides quality scores and candidate rankings that feedback on the input quality, enabling users to correct errors before final submission. This feedback loop resolves the precision issue while maintaining input freedom.
2Ease of operation
If free-form text address input is allowed, then ease of operation is improved, but reliability of address identification deteriorates due to typographical errors and ambiguity
Solution Approach 1:
The system performs preliminary actions by pre-generating candidate addresses from a comprehensive database before final selection. It pre-evaluates multiple potential matches using various quality metrics (string similarity, position accuracy, attribute completeness) and prepares ranked results in advance. This preliminary processing ensures that even erroneous inputs are matched to the correct addresses through pre-computed candidate evaluation.
Solution Approach 2:
The system changes parameters by evaluating addresses across multiple dimensions rather than a single match criterion. It uses weighted quality scores that consider string similarity, position accuracy, completeness of address elements, and other attributes. By changing from a single-parameter exact match to multi-parameter evaluation, the system maintains high reliability despite free-form input variations.
3Measurement precision
If candidate address generation and quality scoring is implemented, then measurement precision of address information is improved, but device complexity increases
Solution Approach 1:
The patent segments the address evaluation process into distinct modular components: address parsing module, candidate generation module, quality evaluation module with multiple attribute assessors (string quality, position quality, completeness), and result ranking module. Each component handles a specific aspect of the evaluation, making the complex system manageable and maintainable while achieving high precision through coordinated operation of these segments.
4Measurement precision
If comprehensive quality evaluation of address attributes is performed, then measurement precision is improved, but loss of time increases due to processing multiple address candidates
Solution Approach 1:
The system applies partial action by evaluating only the most critical quality attributes to a sufficient degree rather than exhaustively analyzing every possible aspect. It uses weighted quality scores that focus on the most discriminative features (string similarity, position accuracy, key element completeness) and stops evaluation when the top candidate clearly exceeds others. This partial evaluation approach achieves high precision without exhaustive processing of all candidates.
Data Source
AI summary
An approach is provided for providing a user with a ranked list of possible physical addresses in response to an address submitted by the user. An address submitted by a user is parsed and a number of possible candidate addresses are generated from the user provided address. The quality of the candidate addresses is ranked according to the quality of their individual address elements and factors applied to these elements. An overall quality score for each candidate address is thereby derived. The list of candidate address is displayed to the user according to overall quality score ranking.