Content Management System Storage Priority Assignment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Media content storage devices often run out of space due to insufficient storage capacity, necessitating a method to automatically determine and allocate available storage space for future media content by managing retention and deletion based on user activity.
Innovation Solution
A Content Management System that tracks previous user activity, such as deletion and viewing selections, to assign retention priorities and determine the quantity of storage space needed, initiating deletion of less prioritized content when storage is low.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If storage capacity is increased to store more media content, then the quantity of stored content is improved, but the device complexity and cost increase
Solution Approach 1:
The system dynamically adjusts storage allocation and deletion policies based on real-time user activity patterns. Retention priorities are not fixed but adapt continuously as user behavior changes, allowing the system to optimize storage utilization without requiring additional hardware capacity.
Solution Approach 2:
The system changes the parameter of retention priority based on user activity analysis. By transforming static storage allocation into dynamic parameter adjustment, the system maximizes the effective use of available storage space without increasing physical capacity.
2Loss of substance
If manual deletion of content is required to free up storage space, then the loss of storage space is improved, but the ease of operation deteriorates
Solution Approach 1:
The system performs self-service by automatically analyzing user activity patterns and deleting content that is unlikely to be viewed again. This eliminates the need for manual user intervention in space management, as the system autonomously maintains adequate storage availability.
Solution Approach 2:
The system implements feedback loops where user viewing and deletion behaviors are continuously monitored and fed back into the retention priority algorithm. This feedback mechanism enables the system to learn from user actions and automatically adjust deletion decisions, removing the burden of manual space management from users.
3Productivity
If automated deletion based on user activity is implemented, then the productivity of storage management is improved, but the measurement precision of user preference detection is required
Solution Approach 1:
The system performs preliminary analysis of user activity patterns to establish retention priorities before deletion decisions are needed. By pre-processing and understanding user behavior in advance, the system can make accurate automated deletion decisions without requiring complex real-time analysis, thus maintaining both productivity and precision.
Data Source
AI summary
Systems, methods and devices are provided for managing media content storage priority and retention in a single- or multi-user environment. Indications of previous user activity are received regarding multiple portions of content stored via one or more storage devices. The previous user activity may include previous user deletion selections and/or previous user viewing selections of one or more of the multiple portions of content. A retention priority may be assigned to portions of media content based on the previous user activity. Responsive to receiving an indication of low available storage space on the one or more storage devices, a quantity of storage space on the one or more storage devices to make available is determined based on the previous user activity. Deletion of one or more portions of currently stored content is initiated based on the determined quantity of storage space to make available.