Address Synthesis from Physical Mail Data
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Solution Overview
Problem
Traditional mail delivery systems face challenges in accurately interpreting and updating addresses, especially in rural areas, due to lack of redundant information and reliance on human knowledge, leading to inefficiencies and errors in sorting and delivery.
Innovation Solution
An apparatus comprising a data collector and address synthesizer that collects data from physical mail items, synthesizes addresses, and generates confidence information to validate address accuracy, using a hierarchical structure to analyze and update link strengths for improved parsing and noise removal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If bottom-up address management processes are used with local delivery agents reporting changes, then address updates can be acquired, but the process is labor intensive with long latency and human errors
Solution Approach 1:
The patent replaces manual bottom-up address management with automated machine-based optical character recognition (OCR) and image processing systems. Mail sort equipment captures images of addresses on physical mail items and automatically extracts and validates address data, eliminating reliance on human delivery agents to report changes manually. This mechanical-to-automated substitution resolves the contradiction by maintaining high address accuracy through machine precision while dramatically reducing change latency through continuous automated processing.
Solution Approach 2:
The system enables address data to be self-updated through automated capture and processing. As mail items pass through sorting equipment, their addresses are automatically imaged, extracted, and added to the address database without human intervention. This self-service mechanism continuously refreshes address information in real-time, eliminating the long latency associated with manual reporting while maintaining accuracy through automated validation processes.
2Productivity
If machine-based address interpretation is implemented, then sorting efficiency improves, but system complexity increases due to need for redundant information and validation
Solution Approach 1:
The patent applies preliminary action by pre-processing and validating address data before it is needed for sorting. The system continuously captures, extracts, and validates address information from physical mail items, building a ready-to-use address database in advance. This preliminary preparation eliminates the need for complex real-time interpretation during sorting, as machines can directly match mail items against pre-validated addresses, thereby improving sorting efficiency without proportionally increasing system complexity.
Solution Approach 2:
The system implements feedback loops where address interpretation results are continuously validated against multiple data sources including third-party address databases and historical mail data. When discrepancies are detected, the system automatically cross-validates and corrects address information. This feedback mechanism simplifies the overall system by providing automated error correction, reducing the need for complex manual validation procedures while maintaining high sorting efficiency through reliable address matching.
3Extent of automation
If optical character recognition is used to read addresses, then automated processing is enabled, but parsing errors increase due to inconsistent address formats
Solution Approach 1:
The patent applies parameter changes by transforming inconsistent address formats into a standardized structure through multiple processing stages. The system uses configurable parameters and validation rules to normalize address components (street names, numbers, postal codes) extracted from OCR data. By dynamically adjusting parsing parameters based on detected address patterns and cross-referencing with known address formats, the system maintains high automated processing capability while significantly improving parsing accuracy despite format variations.
Solution Approach 2:
The system uses a composite approach combining multiple data sources and validation methods to overcome OCR parsing errors. It integrates OCR extracted data with third-party address databases, historical mail data, and format validation rules to create a composite address verification system. This multi-layered composite structure allows the system to maintain high automation while achieving accurate parsing by cross-validating against multiple reference sources and correcting OCR errors through comparative analysis.
Data Source
AI summary
Any of various types of mail management information may be synthesized from data associated with physical mail items. For example, addresses, complete with addressee names, could be synthesized from data collected from physical mail items. Confidence information which indicates a measure of confidence that each synthesized address is a valid address could also be generated from the collected data. Intelligence functions may be provided to enhance address synthesis capabilities. More generally, input data for synthesis of mail management information could include data collected from physical mail items, other mail management information, or both. Features such as service delivery compliance management, network proficiency management, delivery route proficiency management, customer compliance management, a visibility service, address cleansing, delivery notification, addressee verification, synthesis of statistics, and/or synthesis of behavioral patterns could be implemented.