A domain large model-based knowledge base system
By optimizing the user allocation method, and adopting either profile-based allocation or load-based allocation according to the stable state and load status of user profiles, the problem of uneven server load in the knowledge base system was solved, improving operating efficiency and processing speed.
CN120596252BActive Publication Date: 2026-02-27BEIJING XINRUI XIANGTONG TECHNOLOGY CO LTD
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Patent Information
- Application Number
- CN202510679206.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-26
- Publication Date
- 2026-02-27
- Estimated Expiration
- 2045-05-26
AI Technical Summary
Technical Problem
In existing knowledge base systems, a single server allocation method is insufficient to meet user needs, resulting in unbalanced load and affecting operational efficiency.
Method used
The data analysis unit determines the stable state of user profiles based on the continuous proportion of user categories and the number of requests. Combined with the early warning ratio coefficient and load status, it optimizes server resource allocation by adopting profile allocation or load allocation methods.
Benefits of technology
It improves the operational efficiency of the knowledge base system by reducing server load and increasing processing speed and efficiency through precise user allocation.
✦ Generated by Eureka AI based on patent content.
Abstract
The application relates to the technical field of knowledge bases, in particular to a knowledge base system based on a domain large model, which comprises a data processing unit, which carries out data caching and data processing; a data analysis unit, which determines a user portrait stable state according to a user category continuous proportion and a user request frequency, and determines a user allocation mode according to the user portrait stable state; a portrait allocation unit, which determines a server state according to a pre-warning proportion coefficient and a first-class user dispersion, and determines a portrait allocation mode according to the server state; and a load allocation unit, which determines a load state according to a load balancing coefficient and a load balance coefficient, and determines a load allocation mode according to the load state. The application optimizes the user allocation mode, improves the allocation accuracy of the server, and effectively improves the overall operation efficiency of the knowledge base system.
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