Heterogeneous Log Pattern Editing Recommendation System
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Solution Overview
Problem
Manual editing of millions of heterogeneous IT operational logs generated daily in complex systems like IoT and smart cities is infeasible, and existing log analytics tools do not fully meet user demands for pattern modification, deletion, and addition.
Innovation Solution
A computer-implemented method and system that identifies patterns with variable and constant fields, extracts category, cardinality, and before-after n-gram features, generates similarity scores for target fields, and recommends log pattern edits based on these features for network devices generating heterogeneous logs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual monitoring of logs is performed, then user understanding and control over log patterns is improved, but the system becomes infeasible for large numbers of logs
Solution Approach 1:
The system automatically generates pattern recommendations by analyzing log data and identifying patterns without requiring manual user intervention. The recommendation engine self-services by computing similarity scores and proposing edits autonomously, freeing users from manual monitoring while maintaining pattern understanding capabilities
Solution Approach 2:
The patent introduces a recommendation engine as an intermediary between the raw log data and the user. This intermediary automatically analyzes logs, generates pattern recommendations, and presents them to users, bridging the gap between automated processing and user understanding without requiring direct manual monitoring
2Productivity
If automated pattern generation is used, then log processing efficiency is improved, but pattern quality and user requirements fulfillment deteriorates
Solution Approach 1:
The system implements feedback by analyzing user interactions with recommended patterns and using this information to refine future recommendations. The recommendation engine learns from user acceptance or rejection of pattern suggestions, continuously improving pattern quality while maintaining automated processing efficiency
Solution Approach 2:
The patent applies preliminary action by pre-computing pattern recommendations and similarity scores before users need them. The system proactively generates and ranks pattern edit recommendations, so when users review patterns, high-quality suggestions are already prepared, improving both efficiency and pattern quality
3Adaptability or versatility
If pattern editing tools are added, then user capability to modify patterns is improved, but system complexity increases
Solution Approach 1:
The patent segments the pattern editing functionality into distinct, modular components: pattern generation module, similarity computation module, recommendation module, and user interface module. This segmentation allows each component to be independently developed and maintained, reducing overall system complexity while providing comprehensive pattern modification capabilities
Data Source
AI summary
A heterogeneous log pattern editing recommendation system and computer-implemented method are provided. The system has a processor configured to identify, from heterogeneous logs, patterns including variable fields and constant fields. The processor is also configured to extract a category feature, a cardinality feature, and a before-after n-gram feature by tokenizing the variable fields in the identified patterns. The processor is additionally configured to generate target similarity scores between target fields to be potentially edited and other fields from among the variable fields in the heterogeneous logs using pattern editing operations based on the extracted category feature, the extracted cardinality feature, and the extracted before-after n-gram feature. The processor is further configured to recommend, to a user, log pattern edits for at least one of the target fields based on the target similarity scores between the target fields in the heterogeneous logs.