Device Attribute Prediction Model for Network Management GUI
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Solution Overview
Problem
The limited space on graphical user interfaces (GUIs) for network device management restricts the display of device attributes, making it difficult for administrators to create filter conditions, leading to increased management costs and poor user experience.
Innovation Solution
A device management method that utilizes a prediction model trained on configured device attributes to predict and recommend additional attributes, allowing administrators to efficiently configure filter conditions and reduce manual input, thereby improving user experience and management efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If more device attributes are displayed on the GUI to support finer granularity filter conditions, then the system supports more device attributes and improves filtering capability, but the GUI space limitation is exceeded and user interface complexity increases
Solution Approach 1:
The system performs preliminary action by proactively predicting device attributes that users are likely to need for filter conditions, and pre-presents these predicted attributes to users before they have to manually search or input them. This resolves the contradiction by preparing the interface in advance with relevant attributes, maintaining simplicity while supporting comprehensive filtering.
Solution Approach 2:
The system implements self-service by automatically predicting and presenting device attributes based on analysis of user behavior patterns and historical data, without requiring users to manually navigate through all available attributes. The interface serves itself by intelligently selecting what to display, resolving the contradiction between comprehensive attribute support and interface simplicity.
2Ease of operation
If users manually input and search for device attributes to create filter conditions, then filter conditions can be created, but management cost and time consumption significantly increase
Solution Approach 1:
The system performs preliminary action by predicting which device attributes users will need for filter conditions and presenting them in advance. This eliminates the need for users to manually search through all available attributes, significantly reducing the time and effort required to create filter conditions while maintaining ease of operation.
Solution Approach 2:
The system introduces an intermediary mechanism - the attribute prediction model - that acts as a mediator between the user's filtering needs and the comprehensive set of available device attributes. This intermediary intelligently translates user intent into specific attribute recommendations, resolving the contradiction by reducing manual search effort while supporting comprehensive filtering capabilities.
3Ease of operation
If the GUI limits the number of displayed device attributes to maintain simplicity, then user interface simplicity is maintained, but users can only access limited attributes increasing manual input requirements
Solution Approach 1:
The system performs preliminary action by predicting and pre-displaying the specific device attributes that users are most likely to need for their filter conditions. This resolves the contradiction by maintaining interface simplicity (limiting displayed attributes) while improving adaptability (ensuring the right attributes are available), as the system proactively prepares the interface with relevant attributes before user interaction.
Solution Approach 2:
The system applies local quality by making different parts of the attribute space visible at different times based on user needs. Instead of displaying all attributes simultaneously (which would compromise simplicity), the system dynamically adjusts which attributes are visible in the interface based on prediction, resolving the contradiction between simplicity and comprehensive accessibility.
Data Source
AI summary
A device management method, an electronic device, and computer readable medium for presenting to a user device attributes that are more likely to be configured by the user to improve a device management system. The method may include acquiring a first device attribute set related to a plurality of devices. The first device attribute set includes at least one device attribute that has been configured by a user. The method may include determining a second device attribute set related to the plurality of devices. The second device attribute set includes device attributes different from the at least one device attribute described above. The method may include receiving configuration from the user for a device attribute in the second device attribute set and determining a to-be-processed device from the plurality of devices based on the configured device attributes in the first device attribute set and the second device attribute set.