Data Ranking Modification System Using String Midranks
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Solution Overview
Problem
In data management systems, maintaining and updating the ordering of data items is computationally expensive and resource-intensive, especially as the size of the data set grows and/or the frequency of re-ordering increases.
Innovation Solution
The Data Ranking and Modification System (DRS) uses string values for ranking data items, allowing for efficient re-ranking by calculating a midrank between two existing string values, thereby reducing the need for extensive renumbering or re-indexing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional systems use integer ranking values and renumber all affected items when order changes, then the ordering is maintained accurately, but the computational cost and resource consumption increase significantly
Solution Approach 1:
The patent changes the ranking parameter from integer values to string values. This allows for more flexible ranking representations and enables efficient re-ranking by calculating midranks between existing string values, thereby reducing the need for extensive renumbering operations while maintaining ordering accuracy
Solution Approach 2:
The system pre-calculates and stores midrank values between existing rankings. When a re-ranking operation is needed, the system can directly use these pre-computed midranks rather than performing comprehensive renumbering, significantly reducing computational cost while maintaining accurate ordering
2Quantity of substance
If the data set size increases, then more data can be managed, but the computational expense of renumbering increases
Solution Approach 1:
By transitioning from integer to string-based ranking values, the system can handle larger data sets more efficiently. String values allow for midrank calculations that avoid the O(n) renumbering operation, reducing computational cost as data set size increases
Solution Approach 2:
The patent replaces the mechanical process of sequential renumbering with a more elegant string-based midrank calculation system. This substitution eliminates the need to iterate through and renumber all affected records, making the system scalable to larger data sets
3Adaptability or versatility
If re-ordering frequency increases, then the system remains updated with current data order, but the resource consumption increases
Solution Approach 1:
The system pre-computes and stores midrank values between existing rankings. When re-ordering occurs, these pre-computed values can be directly applied without performing comprehensive renumbering operations, reducing resource consumption even with frequent re-ordering
Solution Approach 2:
The string-based ranking system enables efficient handling of frequent re-ordering operations through midrank calculations. This approach avoids the resource-intensive process of renumbering all affected items, allowing the system to adapt to frequent changes with minimal resource consumption
Data Source
AI summary
Various embodiments for a data ranking and modification system are described herein. An embodiment operates by receiving a selection to organize a plurality of items displayed on the user interface, including at least a first item, a second item, and a third item. It is determined that the plurality of items that are ranked relative to each other. A re-ranking of the first item is detected, the re-ranking moving the first item between the second item and the third item. A midrank between a second rank of the second item and a third rank of the third item is calculated. The midrank is assigned to a first rank of the first item. The first item is automatically moved between the second item and the third item on the user interface based on a comparison of the first rank, second rank, and third rank.