Personalized Home Page Interface Recommendation for O&M Platforms
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Solution Overview
Problem
Operation and maintenance platforms have fixed home pages that do not meet the diverse needs of personnel, leading to low efficiency due to frequent clicks and interface jumps.
Innovation Solution
A method that monitors user behavior to generate personalized home page interface recommendations by updating user and character models based on click-through frequencies, residence times, and operation times, calculating interface recommendation probabilities, and generating tailored links for new and regular users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If fixed existing functions are shown on home pages, then platform structure is simple and stable, but operation and maintenance efficiency deteriorates due to frequent clicks and interface jumps
Solution Approach 1:
The patent implements dynamic home page interfaces that automatically adjust their content and layout based on user behavior patterns. The system monitors operation logs and dynamically generates personalized interface recommendations, transforming the static fixed-function home page into a dynamic adaptive interface that evolves with user needs, thereby improving efficiency without requiring complex manual reconfiguration
Solution Approach 2:
The system employs automated algorithms to analyze user behavior data and generate interface recommendations without manual intervention. The platform self-adjusts by monitoring click patterns, residence times, and operation frequencies, then automatically updates user models and generates personalized home page configurations, eliminating the need for manual platform restructuring while improving operational efficiency
2Adaptability or versatility
If fixed home pages are used, then platform maintenance is easy, but user needs of different characters and users cannot be met
Solution Approach 1:
The patent implements personalized home pages tailored to different user characters and individuals. By analyzing user behavior data and generating character-specific and user-specific interface recommendations, the system provides locally optimized interfaces for different user groups rather than a uniform fixed layout, thereby enhancing adaptability to diverse user needs while maintaining centralized algorithmic control for ease of maintenance
Solution Approach 2:
The system pre-processes user behavior data and builds user models in advance to predict and prepare personalized interface recommendations. By continuously updating user models based on historical operation logs before users actually need specific interfaces, the platform proactively configures optimal home pages, enabling quick adaptation to user needs without real-time maintenance intervention
3Loss of time
If frequent clicks and interface jumps are required, then users can reach target interfaces, but operation time increases and efficiency decreases
Solution Approach 1:
The system pre-calculates and pre-positions frequently accessed interfaces directly on personalized home pages based on user behavior analysis. By analyzing operation logs to identify commonly accessed interfaces and proactively placing them on users' home pages, the system eliminates the need for multiple clicks and interface jumps, thereby reducing operation time while maintaining ease of access to target interfaces
Solution Approach 2:
The patent implements a feedback loop where user interaction patterns are continuously monitored and fed back into the recommendation algorithm. By tracking clicks, residence times, and operation sequences, the system learns from user behavior and continuously optimizes home page configurations to minimize navigation steps, thereby reducing operation time while adapting to evolving user preferences and maintaining operational ease
Data Source
AI summary
Disclosed in the present application is a home page interface recommendation method for an operation and maintenance platform. In the method, a home page recommendation interface is automatically learned and intelligently generated on the basis of daily operation behavior habits of different roles and different users, such that no matter a new user or an old user may obtain home page recommendation conforming to his/her positioning, the use efficiency of the operation and maintenance personnel on the operation and maintenance platform is greatly improved, the operation and maintenance time is shortened, and the cost is reduced. In addition, the present application also provides a home page interface recommendation apparatus and device for an operation and maintenance platform, and the technical effects of the home page interface recommendation apparatus and device correspond to the technical effects of the method.