Knowledge base content sharing and learning system and method based on distributed network environment

Abstract

The invention provides a knowledge base content sharing and learning system and method based on a distributed network environment. Through the knowledge base content sharing and learning system and method, efficient and secure transmission of knowledge in a knowledge base among distributed nodes is realized, and the hit rate of retrieval of the knowledge in the knowledge base is increased by the adoption of a machine learning algorithm. The system comprises center nodes and child nodes in communicating connection. The center nodes include a message queue server, a knowledge base management system, a search engine server and a machine learning server, wherein the message queue server is used for uploading and issue of the knowledge; the knowledge base management system is used for input andreview of the knowledge; the search engine server is used for knowledge retrieval; and the machine learning server is used for correcting the knowledge retrieval order. The child nodes include a knowledge base management system, a search engine server and a machine learning server in communicating connection. According to the method, the knowledge in the knowledge base provides rich text editingand uploading; vertical bidirectional sharing and horizontal management are performed on the knowledge in the knowledge base; and a search training mechanism is established through the machine learning algorithm to correct the knowledge retrieval order.

Description

technical field [0001] The invention relates to knowledge base content sharing and learning, in particular to a system and method for knowledge base content sharing learning based on a distributed network environment. Background technique [0002] Distributed network deployment is characterized by connecting machines in different physical environments to form a large local area network through network connections. The generation of distributed networks is of great significance. Distributed networks are distributed in different locations and have multiple terminals In the distributed network, each network is controlled independently, and the central control center only needs to perform overall scheduling. In the distributed system, the concept of centralized control is not emphasized, and there is a distributed system based on the global control center. Layer control structure, but each distributed network has a high degree of autonomy. The distributed network greatly reduces...

AI Technical Summary

Problems solved by technology

[0003] With the rapid development of the information age, the traditional single-deployed plain text knowledge base has gradually failed to meet the actual needs. For this reason, the knowledge base based on distr

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