Assisted Problem Remediation via Quantitative Process Attributes
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Solution Overview
Problem
Current methods for selecting computer problem remediation processes often rely on human judgment, lacking data-driven decision-making, which limits the sharing of knowledge and efficiency in problem resolution.
Innovation Solution
A method that computes and presents quantitative data on remediation processes using process description languages like WS-BPEL, facilitating informed choices among remediation agents by characterizing candidate processes with attributes such as time, risk, and scope of change.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If human agents make decisions based on personal observation and episodic knowledge, then decision-making can be performed without additional data collection, but knowledge cannot be shared among agents and decision quality is limited
Solution Approach 1:
The patent creates a centralized knowledge base that copies and stores remediation process data from multiple sources. This centralized repository can be accessed by all agents, eliminating the need for each agent to rely solely on personal observation while enabling knowledge sharing across the entire organization.
Solution Approach 2:
The patent introduces a centralized data collection system and knowledge base as an intermediary between individual agents and the remediation processes they perform. This intermediary collects, stores, and distributes information, allowing agents to access shared knowledge without directly interacting with each other or duplicating data collection efforts.
2Measurement precision
If multiple candidate remediation processes are evaluated using multiple criteria, then more informed decisions can be made, but the complexity of evaluating and comparing processes increases
Solution Approach 1:
The patent transforms multiple evaluation criteria (simplicity, risk, effectiveness, speed, scope of change, cost) into standardized quantitative parameters with consistent scales. This allows for systematic comparison of candidate processes across all criteria while maintaining evaluation precision, as each process is assessed against the same parameter framework.
Solution Approach 2:
The patent divides the complex evaluation process into separate, manageable components. Each remediation process is evaluated independently against multiple criteria, with results stored and then compared systematically. This segmentation allows agents to handle complex multi-criteria evaluation by breaking it down into individual attribute assessments that can be processed and compared separately.
3Productivity
If comprehensive data about remediation processes is collected and analyzed, then better selection decisions can be made, but the time and resources required for data processing increase
Solution Approach 1:
The patent collects and processes remediation process data in advance, storing it in a centralized knowledge base before it is needed for decision-making. By performing data collection and preliminary analysis beforehand, the system eliminates the need for time-consuming data gathering during actual remediation situations, thus improving response time while maintaining comprehensive data analysis.
Data Source
AI summary
A method (which can be computer implemented) for assisted remediation of at least one problem with a computer system includes the steps of obtaining data from the computer system, the data being indicative of the at least one problem; hypothesizing at least a first candidate remediation process for the problem from among a plurality of annotated remediation process descriptions, based at least in part on the data; associating at least a first attribute with the at least first candidate remediation process; and facilitating presentation of the at least first candidate remediation process with the associated attribute to a remediation agent.