Dynamic IT Recommendation Framework for System Performance
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing IT system management tools fail to provide comprehensive recommendations that consider the entire system and its components, lacking feedback integration from administrators, which limits their effectiveness in managing complex IT systems.
Innovation Solution
A self-evolving recommendation framework that dynamically recommends tasks to system administrators based on predicted outcomes, tracks the impact of these tasks, and solicits both explicit and implicit feedback to improve future recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If existing tools evaluate a single component in the system, then the recommendation process is simple and fast, but the recommendations do not consider impact on other system components or the system as a whole
Solution Approach 1:
The patent segments the IT system into multiple components (hardware, software, network, etc.) and evaluates each component's impact separately before synthesizing comprehensive recommendations. This allows the system to consider the entire system while maintaining manageable analysis through structured segmentation of system elements.
Solution Approach 2:
The patent creates a universal recommendation framework that can evaluate multiple system components and generate recommendations applicable across different IT environments. The system integrates various evaluation methods and data sources into a single comprehensive tool that adapts to different system configurations and administrative needs.
2Adaptability or versatility
If existing tools do not incorporate administrator feedback, then the tool operation is simple, but the recommendations do not evolve with system growth and complexity
Solution Approach 1:
The patent implements explicit feedback mechanisms where administrators can provide input on recommendation quality, and implicit feedback through tracking administrator actions and system performance changes. This feedback is systematically integrated to continuously improve and adapt recommendations to the specific IT environment and administrative preferences.
Solution Approach 2:
The patent creates a dynamic recommendation system that evolves over time by incorporating feedback and adapting to changing system conditions. The system adjusts its evaluation criteria and recommendation strategies based on accumulated data and administrator interactions, making it adaptable to system growth and complexity.
3Reliability
If a comprehensive system evaluation is performed, then the recommendations consider the entire system, but the analysis time and processing requirements increase
Solution Approach 1:
The patent performs preliminary data collection and system assessment to establish a baseline understanding of the IT environment. By gathering and organizing system information in advance, the framework reduces the time required for comprehensive evaluation when generating recommendations, as much of the foundational analysis is already completed.
Solution Approach 2:
The patent implements continuous monitoring and evaluation of system parameters, maintaining an ongoing assessment of system state. This continuous action allows the system to build upon previous analyses rather than starting from scratch, reducing redundant computation and accelerating recommendation generation while maintaining comprehensive system evaluation.
Data Source
AI summary
Embodiments are provided for managing performance of a computer system. Both implicit and explicit recommendations for processing of tasks are provided. System performance is tracked and evaluation based upon the actions associated with the task. Future recommendations of the same or other tasks are provided based upon implicit feedback pertaining to system performance, and explicit feedback solicited from a system administrator.