Event Clustering System for Web Information Management
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Solution Overview
Problem
Current systems for managing and organizing vast amounts of web-based information, such as email and communication messages, lack effective automated techniques for indexing and retrieval, leading to difficulties in finding relevant information due to the impracticality of manual folder organization and the limitations of existing clustering and classification methods, which are not conducive to user behavior and are vulnerable to spam and data loss in network traffic monitoring.
Innovation Solution
A system with multiple lower tier levels coupled to a top tier level allows for independent management and data separation, enabling multi-system interaction, consolidation, and aggregation of information from lower tiers to a higher tier, while preventing cross-tier entanglement, using event clustering and signalization engines to group and analyze messages, and employing NMF and k-means algorithms for data processing and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual folder organization is used to manage web-based information, then information can be stored in folders of appropriate topics, but it becomes impractical to handle massive amounts of information and difficult to locate relevant information efficiently
Solution Approach 1:
The system automatically indexes and organizes web-based information without requiring manual user intervention. The indexing engine autonomously processes incoming messages and events, assigning them to appropriate hierarchical categories based on content analysis, thereby eliminating the impracticality of manual folder organization for massive information volumes
Solution Approach 2:
The system performs preliminary indexing and classification of information as it arrives, rather than requiring users to organize information later. By pre-organizing data into hierarchical categories with automated metadata tagging, the system enables efficient retrieval without requiring users to understand the entire directory hierarchy or semantics of information
2Productivity
If automated indexing techniques are implemented to organize web-based information, then information retrieval becomes more efficient, but the system becomes vulnerable to spam and data loss in network traffic monitoring
Solution Approach 1:
The system introduces an intermediary filtering layer between network traffic and the indexing engine. This intermediary component analyzes incoming messages for spam characteristics before they reach the automated indexing system, preventing spam from compromising data integrity while allowing legitimate information to be processed and organized efficiently
Solution Approach 2:
The system implements protective measures in advance by incorporating spam filtering and validation mechanisms before information enters the automated indexing process. This beforehand cushioning ensures that the automated organization system remains reliable and resistant to spam and data loss vulnerabilities
3Adaptability or versatility
If hierarchical web directories are created to organize information, then information can be categorized into directories, but the process is not automated and requires understanding of the entire directory hierarchy and semantics
Solution Approach 1:
The automated indexing engine performs self-service by autonomously analyzing information content and assigning it to appropriate hierarchical categories without requiring user understanding of the directory structure. The system independently processes metadata extraction, content analysis, and categorical placement, making the adaptability of hierarchical organization accessible without operational complexity
Solution Approach 2:
The system replaces the mechanical process of manual directory navigation and understanding with an automated computational indexing mechanism. By substituting human cognitive processes with algorithmic content analysis and automated categorization, the system maintains the versatility of hierarchical organization while eliminating the requirement for users to understand the entire directory hierarchy and semantics
4Device complexity
If a single tier system is used for information management, then the system structure is simple, but it cannot provide independent management and data separation for multi-system interaction
Solution Approach 1:
The system segments information management into multiple hierarchical tiers, where each tier represents a distinct level of abstraction and management autonomy. This segmentation enables independent management of different data domains while maintaining overall system coherence, allowing multi-system interaction through defined interfaces between tiers without requiring a single monolithic structure
Solution Approach 2:
The system transitions from a single-dimensional flat structure to a multi-dimensional hierarchical tiered architecture. By adding the dimension of hierarchical levels, the system achieves both structural organization and multi-system interaction capability, where each tier operates semi-independently while contributing to the overall system functionality
Data Source
AI summary
An event clustering system includes a processor. An extraction engine is in communication with an infrastructure. The extraction engine receives data from the infrastructure. A signalizer engine includes one or more of an NMF engine, a k-means clustering engine and a topology proximity engine. The signalizer engine determines one or more common steps from events and produces clusters relating to the alerts and or events. In response to production of the clusters one or more physical changes are made in a managed infrastructure hardware. Multi-systems interact with each other.