Natural Language Network Query Processing for Tenant-Specific Troubleshooting
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Solution Overview
Problem
Managing and troubleshooting networks with diverse network-connected devices is challenging due to their varying network-related attributes and addresses.
Innovation Solution
A network access control and management server utilizing natural language processing to receive queries, classify user intent, extract named entities, and provide tenant-specific network-related responses, enabling efficient network management and troubleshooting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional network management methods are used to manage diverse network devices, then comprehensive device control is achieved, but system complexity and difficulty of operation increase significantly
Solution Approach 1:
The patent introduces a natural language processing interface as an intermediary between the user and the complex network management system. This mediator translates simple user queries into structured commands that the backend system can process, eliminating the need for users to directly interact with complex technical parameters and device configurations.
Solution Approach 2:
The patent replaces traditional mechanical interaction methods (manual configuration interfaces, command-line inputs, device-by-device management) with an automated natural language processing system. This substitution allows the system to automatically parse, interpret, and execute network management tasks based on conversational input, significantly reducing operational complexity.
2Difficulty of detecting and measuring
If detailed network attributes and addresses are tracked for each device, then network troubleshooting capability is improved, but information processing complexity and time increase
Solution Approach 1:
The patent implements preliminary action by pre-processing and organizing network device information into structured formats before troubleshooting is needed. The system maintains organized records of device attributes, relationships, and configurations in advance, allowing rapid retrieval and analysis when troubleshooting queries are submitted, rather than gathering information in real-time during incidents.
3Ease of operation
If natural language processing is implemented for network queries, then ease of use is improved, but processing complexity and computational requirements increase
Solution Approach 1:
The patent applies segmentation by breaking down the natural language processing task into distinct modular components: intent recognition module, entity extraction module, query parsing module, and response generation module. Each module handles a specific aspect of the processing pipeline, allowing the system to manage complexity through functional decomposition and enabling independent optimization of each component.
Data Source
AI summary
A method of operating a network is provided that includes receiving a query, using a first language model to determine an intent or purpose of the query, using a second language model to extract a named entity from the query, and obtaining search results by searching for the extracted named entity on a named entity list corresponding to a particular tenant. The method can further include generating a response based on the search results. The query can be a natural language query, and the first language model can be a natural language model. The second language model for extracting the named entity can be a network-related language model that is trained on network records associated with a plurality of tenants. The network records associated with the plurality of tenants can be stored on a multi-tenant database.