Directed Graph Generation from Raw Data Using Data Extrapolation
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Solution Overview
Problem
Current methods for creating directed graphs are limited by manual or static processes, making them inflexible in dynamic data environments.
Innovation Solution
An apparatus and method that uses a processor to receive raw data, determine execution elements, and generate a directed graph through data extrapolation, forming an ordered series of elements connected by operation data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual or static processes are used to create directed graphs, then the process is simple and controllable, but the adaptability to dynamic data environments is limited
Solution Approach 1:
The patent implements a dynamic graph generation system that automatically adapts to changing data environments. The processor continuously receives raw data, determines execution elements, performs data extrapolation, and generates directed graphs that reflect current data relationships. This dynamic approach allows the system to respond to real-time data changes without manual intervention, resolving the contradiction between adaptability and complexity by automating the graph generation process.
Solution Approach 2:
The system performs self-service through automated data processing. The processor automatically determines execution elements from raw data, calculates data extrapolation, and generates directed graphs without requiring manual input or intervention. This automation enables the system to adapt to dynamic data environments independently, improving adaptability while managing complexity through standardized automated workflows.
2Adaptability or versatility
If manual processes are used to create directed graphs, then the graph structure is simple and easy to control, but the flexibility in dynamic data environments is reduced
Solution Approach 1:
The patent replaces manual mechanical processes with automated computational mechanisms. Instead of manually creating graph structures, the system uses processors and algorithms to automatically determine execution elements, perform data extrapolation, and generate directed graphs. This substitution maintains ease of operation through automation while significantly improving flexibility and adaptability to dynamic data environments.
3Reliability
If static processes are used to generate directed graphs, then the generation process is stable and predictable, but the relevance to changing data environments is reduced
Solution Approach 1:
The system incorporates feedback mechanisms where the processor continuously receives raw data from data sources, determines execution elements based on current data relationships, performs data extrapolation, and generates updated directed graphs. This feedback loop ensures the generation process remains stable through standardized algorithms while adapting to changing data environments, maintaining relevance through continuous updates driven by incoming data.
Data Source
AI summary
An apparatus and method of generating directed graph using raw data are disclosed. The apparatus includes at least a processor and a memory communicatively connected to the at least a processor, wherein the memory contains instructions configuring the at least a processor to receive raw data from one or more data sources, determine a plurality of execution elements from the raw data, determine a data extrapolation of the plurality of execution elements, wherein determining the data extrapolation further includes determining at least an operation datum for the plurality of execution elements and generate a directed graph as a function of the data extrapolation, wherein the directed graph comprises an ordered series of the plurality of execution elements connected using the at least an operation datum.