Alert Analysis System Classifying Comments by Fluctuation Phase
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Solution Overview
Problem
Conventional alert analyzing systems fail to effectively utilize manager's know-how for predicting and addressing future alerts, as they lack techniques for outputting causal analyses and countermeasures for alerts with common characteristics, and do not efficiently provide comments for later analyses.
Innovation Solution
An alert analyzing apparatus that stores and classifies comments based on time-of-day information and fluctuation phases of monitoring data, allowing for efficient retrieval and display of comments for improving prediction accuracy and addressing alerts with similar characteristics, including traffic, staff, and cost alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manager analyzes individual alerts manually, then cause analysis and countermeasure provision is achieved, but manager's know-how cannot be utilized for future alerts and prediction accuracy cannot be improved
Solution Approach 1:
The system creates a digital copy of the manager's know-how by storing comments and classifying them according to alert characteristics. This copied information can then be automatically retrieved and applied to future alerts, eliminating the need for manual analysis while maintaining prediction accuracy.
Solution Approach 2:
The system implements feedback by storing manager comments on alerts and using this information to improve future predictions. The classified comments serve as feedback that enhances the system's ability to predict and analyze alerts automatically in the future.
2Loss of information
If manager provides countermeasure for each alert, then immediate problem resolution is achieved, but useful information for other alerts with common characteristics is not output
Solution Approach 1:
The system segments the manager's know-how by classifying comments into different categories based on alert characteristics such as time of day and fluctuation phase. This segmentation allows the information to be systematically organized and retrieved for specific types of alerts, improving both information retention and utilization efficiency.
Solution Approach 2:
The classified comment database serves multiple functions: it stores manager know-how, provides information for future alert analysis, and enables automatic retrieval of relevant information. This multi-functionality transforms individual alert responses into a universal knowledge base that benefits all alert analyses.
3Ease of operation
If alert information is stored without classification, then storage is simple, but retrieval of relevant information for future analysis is inefficient
Solution Approach 1:
The system segments comments into classified categories based on alert characteristics (time of day, fluctuation phase). This segmentation makes retrieval easier by organizing information logically, while the automated classification process prevents excessive complexity in the storage structure.
Data Source
AI summary
An alert analyzing apparatus includes: a storage unit that stores a first value and a preset second value in association with time-of-day information, the first value fluctuating as time elapses; an alert output unit that outputs an alert and time-of-day information in a case in which the first value diverges from the second value in a certain time of day; a comment accepting unit that accepts an input of a comment on the alert thus output, and stores the comment in association with the time-of-day information; and a classification unit that classifies a plurality of time zones into any one of predetermined segments, and stores the comment associated with the time zone thus classified, in association with each of the segments, based on a fluctuation phase of the first value.