Automated Event Record Classification for Knowledge Generation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for managing events in computer systems rely heavily on expert knowledge and manual analysis of event records, which is inefficient and cannot process large amounts of historical data effectively.
Innovation Solution
A computer-implemented method that classifies notes from event records into content types and semantic types using content analysis and syntactic parsing, generating knowledge items automatically to manage events by identifying symptoms and resolutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of event records by technical engineers is used, then knowledge items can be generated with high accuracy, but the processing efficiency is low and large amounts of historical data cannot be processed effectively
Solution Approach 1:
The patent introduces an intermediary system comprising a note classifier and paragraph classifier that automatically processes event records. The note classifier extracts notes from event records and classifies them into semantic types, while the paragraph classifier further categorizes paragraphs into content types. This intermediary automated classification system bridges the gap between raw event records and knowledge item generation, enabling efficient processing of large volumes of data while maintaining accuracy through structured classification.
Solution Approach 2:
The patent replaces the mechanical manual analysis process with an automated computational system. Instead of technical engineers manually examining event records, the system uses automated note classification and paragraph classification algorithms to extract and categorize information. This substitution of mechanical human analysis with automated computational processing significantly improves productivity while maintaining measurement precision through consistent application of classification rules.
2Productivity
If automated processing of event records is implemented, then processing efficiency improves, but the complexity of the system increases
Solution Approach 1:
The patent segments the event record processing system into distinct functional modules: a note classifier module that extracts and classifies notes into semantic types, and a paragraph classifier module that categorizes paragraphs into content types. This segmentation allows each module to perform a specific classification function independently, simplifying the overall system architecture while maintaining high processing efficiency. The modular structure reduces system complexity by dividing the complex task of event record analysis into manageable, specialized components.
3Reliability
If manual knowledge base maintenance is used, then knowledge quality is high, but the time consumption for updating and managing knowledge items is excessive
Solution Approach 1:
The patent implements a self-service mechanism where the classification system automatically generates and updates knowledge items from event records without requiring manual intervention. The note classifier and paragraph classifier work together to extract relevant information, categorize it into appropriate semantic and content types, and populate the knowledge base automatically. This self-service approach maintains knowledge quality through consistent classification rules while eliminating the time-consuming manual maintenance process.
Data Source
AI summary
Embodiments of the present invention relate to methods, systems, and computer program products for event management. In a method, a plurality of notes that are comprised in a plurality of event records are obtained in a computer system. A plurality of paragraphs that are comprised in the plurality of notes are classified into a plurality of content types based on a content analysis of the plurality of paragraphs. The plurality of notes are classified into a plurality of semantic types based on the plurality of content types and a syntactic parsing to the plurality of notes. A knowledge item is generated for managing an event in the computer system based on a group of notes in the plurality of notes that are classified into the plurality of semantic types. With these embodiments, knowledge items for managing events may be obtained in an easier and more effective way.