Data Management System Storage Prioritization via NLP Classification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Computing devices face challenges in managing limited storage capacity, which can limit the use of data and computer-implemented services, especially in contexts like healthcare where data is critical for services.
Innovation Solution
A data management system that classifies data based on relevance and quality requirements, prioritizing storage for more useful data and temporarily denying storage for less useful data to optimize limited storage resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all data is stored to ensure complete service provision, then data availability is improved, but storage capacity is exhausted
Solution Approach 1:
The patent applies local quality by classifying data into different categories (e.g., high-value medical data, low-value administrative data) and applying different storage policies to each category. Critical healthcare data receives priority storage while less important data is subject to deletion, thereby optimizing storage capacity allocation based on data-specific characteristics rather than treating all data uniformly.
Solution Approach 2:
The system dynamically changes storage parameters by adjusting retention periods, storage priorities, and deletion thresholds based on data classification results. For example, the system may set longer retention periods for critical patient records while implementing shorter retention for routine administrative data, thereby adapting storage behavior to data value parameters.
2Quantity of substance
If data is selectively deleted to free storage space, then storage capacity is improved, but data loss occurs
Solution Approach 1:
The system performs preliminary classification and evaluation of data value before deletion occurs. By pre-identifying low-value data through automated classification algorithms and quality metrics, the system ensures that only appropriate candidates for deletion are selected, preventing accidental loss of critical information while freeing storage space.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors storage capacity and data access patterns, adjusting deletion decisions based on real-time information. If previously deleted data shows signs of being重新 accessed or valued, the system can reverse deletion decisions, thereby preventing permanent data loss while maintaining storage efficiency.
3Reliability
If manual data management is used to prioritize important data, then data relevance is improved, but operational complexity increases
Solution Approach 1:
The system enables self-service by automatically classifying and prioritizing data based on predefined criteria and algorithms without requiring manual intervention. The automated classification engine evaluates data attributes, assigns relevance scores, and manages storage priorities autonomously, thereby maintaining high data relevance while eliminating operational complexity associated with manual data management.
Solution Approach 2:
The patent replaces manual mechanical data management processes with automated computational systems. Instead of human operators manually sorting and prioritizing data, the system uses algorithmic classification, machine learning models, and automated decision-making processes to achieve the same or better results with reduced operational complexity.
Data Source
AI summary
Methods, systems, and devices for providing computer implemented services are disclosed. To provide the computer implemented services, a storage space in a data management system may be managed. To manage the storage system, data may be obtained for storage. The data may be classified as being related to at least one topic, and quality requirements may be identified based on the at least one topic. A determination may be made, based on the quality requirements, regarding whether the data meets the quality requirements. If the quality requirements are not met by the data, then storage of the data may be denied temporarily. Otherwise, if the quality requirements are met by the data, then the data may be stored.