Automated Duplicate Identification via Flattened Data Arrays
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Solution Overview
Problem
The challenge in identifying duplicate electronic data interchange (EDI) submissions across varying formats and positions within large datasets, leading to manual processes that are time-consuming and error-prone, particularly in industries like insurance where incorrect payouts can occur.
Innovation Solution
An automated method that flattens data values from multiple data fields into structured arrays or linked lists to identify exact or partial matches between information objects, enabling efficient comparison and reducing manual intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processes are used to identify duplicate EDI submissions, then accuracy can be maintained through human review, but time consumption increases significantly and error rates rise due to large data volumes
Solution Approach 1:
The patent replaces manual mechanical review processes with automated computer-based systems that use data structure transformations and algorithmic comparisons to identify duplicates, eliminating human time constraints while maintaining systematic accuracy through programmed logic
Solution Approach 2:
The system transforms data from traditional tabular formats into flattened array structures, changing the fundamental parameter of data organization to enable more efficient computational comparison and duplicate detection across large volumes of EDI submissions
2Device complexity
If data is stored in traditional tabular formats with fixed positions, then data structure simplicity is maintained, but duplicate identification becomes complex when information positions vary across submissions
Solution Approach 1:
The patent segments data from multiple fields into separate array elements, breaking down complex tabular structures into discrete, comparable units that can be independently analyzed for duplicates regardless of their original positional context
Solution Approach 2:
The system transitions from two-dimensional tabular data structures to one-dimensional flattened arrays, adding a dimensional transformation that enables flexible matching algorithms to compare data values independent of their source position or format
3Productivity
If automated systems are implemented for duplicate identification, then processing speed increases for large datasets, but system complexity increases due to varying data formats and positions
Solution Approach 1:
The patent creates a universal data transformation framework that can handle various EDI submission formats and structures through a single flattened array approach, enabling the automated system to process diverse data types without requiring format-specific complexity
Solution Approach 2:
By fundamentally changing the data structure parameter from fixed-position tables to flexible flattened arrays, the system achieves automated high-speed processing capability while reducing the complexity of handling varying formats through a unified structural approach
Data Source
AI summary
Systems and methods are configured to determine whether a particular information object is a duplicate of an object found in separate information objects. In various embodiments, the particular information object and each separate information object includes a set of data fields for storing data values that allows identical values to be stored in different fields for the objects. The data values for the particular information object are combined to form a data structure that includes a data element for each value. A determination as to whether the particular information object is an exact or partial match of a separate information object is made by performing a function on the data structure for the particular information object and a data structure for the separate information object to identify an intersection that includes data values for the particular information object that have an identical match with values for the separate information object.