Temporal Correlation of Discrete and Continuous Data Values
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Solution Overview
Problem
Current database systems face challenges in correlating data values for multiple conditions, particularly when dealing with discrete and continuous value property measurements, leading to incorrect inclusion or exclusion of patients in query results due to timestamp discrepancies.
Innovation Solution
A method is introduced to temporally correlate data values by determining the point in time for each data value, generating approximated values for missing data points, and using these values to evaluate query conditions, ensuring that data values for both conditions are recorded at the same time, thereby improving query processing accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If data values are recorded with timestamps indicating point-in-time measurements, then data collection is simplified and storage is efficient, but query processing accuracy deteriorates when correlating multiple conditions with different timestamps
Solution Approach 1:
The system performs preliminary action by generating approximated values for continuous value fields before query execution. When a query requires correlation of discrete and continuous values, the system proactively creates approximated continuous values at the timestamps of discrete measurements, enabling accurate correlation without requiring complex real-time adjustments during query processing.
Solution Approach 2:
The patent introduces approximated values as an intermediary between discrete measurements and continuous value fields. These approximated values act as a bridge that allows the query processor to correlate discrete and continuous data at different timestamps, resolving the contradiction between simple timestamp-based storage and accurate multi-condition query processing.
2Quantity of substance
If the database stores only discrete measurements with timestamps, then storage requirements are minimized and data entry is simplified, but the ability to correlate multiple conditions deteriorates
Solution Approach 1:
The system generates approximated values in advance for continuous fields based on available discrete measurements. This preliminary computation enables the database to support complex multi-condition queries without requiring continuous data streams or expanded storage structures, maintaining storage efficiency while gaining query correlation capability.
Solution Approach 2:
The patent changes the parameter representation by creating approximated values that transform discrete timestamped measurements into continuous value representations at specific time points. This parameter transformation enables the database to correlate multiple conditions without changing the fundamental discrete nature of the stored data, maintaining storage efficiency while enabling versatile query processing.
3Productivity
If the query engine compares data values without temporal correlation, then query processing speed is maintained, but the reliability of query results deteriorates due to incorrect inclusion or exclusion of records
Solution Approach 1:
The system performs preliminary computation of approximated values at the time of data insertion or on-demand, so that when queries execute, the correlated data is already prepared. This eliminates the need for complex real-time temporal matching during query processing, maintaining high query processing speed while ensuring reliable results through accurate temporal correlation.
Data Source
AI summary
A method, article of manufacture, and apparatus for processing continuous value data is disclosed. Data values stored in a database reflect a measurement of the value obtained for a specific point in time. In order to correlate the evaluation of two or more conditions, when measurements for each condition recorded at the same points in time are unavailable, embodiments of the invention provide a method for generating approximations of the unavailable values for comparison with others. Thereafter, a comparison between values for the points in time may be used to correlate the two conditions during query processing.