Receipt Categorization via Image Recognition and Location Analytics
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Solution Overview
Problem
Traditional financial management systems fail to adequately import and categorize financial documents, particularly paper receipts that are scanned or photographed, due to inadequate analytics methods, leading to faulty expense categorization and mismanagement of finances.
Innovation Solution
A method and system that utilize image recognition engines, analytics modules, and externally generated metadata to identify and categorize financial documents, including receipts, by extracting location information and determining the establishment name, and sorting transactions into appropriate categories based on this information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional OCR-based analytics methods are used to read receipts, then the system can process electronic documents, but the system fails to properly categorize receipts that are crumpled or wrinkled, leading to faulty expense categorization
Solution Approach 1:
The patent introduces an intermediary system that bridges the gap between OCR output and meaningful categorization. The system uses multiple data sources (GPS location, camera images of establishments, transaction timestamps) as mediators to interpret OCR results and determine accurate categorization, rather than relying on OCR alone
Solution Approach 2:
The patent replaces the mechanical OCR reading system with a more sophisticated analytics approach that substitutes physical text recognition with computational analysis of multiple data dimensions (spatial, temporal, visual, and textual information) to determine categorization
2Device complexity
If the system relies solely on OCR to read receipt text, then the processing method is simple, but the system cannot properly read crumpled or wrinkled receipts, leading to mismanagement of finances
Solution Approach 1:
The patent merges multiple information sources (OCR text extraction, GPS location data, camera images of establishments, transaction timestamps) into a unified analytics system. This combination allows the system to cross-validate and supplement each other, ensuring complete and accurate expense information capture
Solution Approach 2:
The patent adds new dimensions to the receipt processing system beyond simple text recognition. It incorporates spatial dimensions (GPS coordinates, establishment location), temporal dimensions (transaction timing), and visual dimensions (camera images of establishments) to create a multi-dimensional analytics approach
3Device complexity
If traditional financial management systems are used, then the system structure is simple, but the system lacks the ability to properly categorize financial documents, leading to wasted time and mismanagement
Solution Approach 1:
The patent implements self-service functionality where the system automatically performs categorization, validation, and enrichment of expense data without requiring manual user intervention. The analytics engine autonomously processes receipts, determines categories, and manages financial data, freeing users from time-consuming manual tasks
Data Source
AI summary
Systems and methods for mapping an electronic document to a particular transaction category are disclosed. An example method may be performed by one or more processors of a categorization system and include receiving, from a user via an interface, an electronic document associated with a transaction between the user and a particular establishment, receiving, from the user via the interface, an image of the particular establishment, identifying in the image, using an image recognition engine, at least one of a sign or a symbol representative of the particular establishment, extracting, using an analytics module, location information from at least one of the image or a mobile device, determining, using the analytics module, a name of the particular establishment based on at least one of the location information or the at least one sign or symbol, and mapping the electronic document to a particular transaction category based on the determined name.