Learning big data search management method

Abstract

The invention discloses a learning big data search management method, which comprises the following steps of checking the user information, and opening a corresponding search interface according to the user information; making a query request by a user, analyzing the intention of the query request according to the keyword, segmenting the keyword, and extracting a subject term and an auxiliary term; matching the query subject term with a historical query network, analyzing according to a matching result, extracting a corresponding encrypted file, and completely matching the matching result, ifthe matching result is complete, indicating that the new query request of the user only has the subject term. The invention discloses a learning big data search management method. Compared with an RSAalgorithm and an AES algorithm, the AES and RSA hybrid algorithm has remarkable advantages in the aspects of encryption safety, low delay, password ciphertext synchronization and the like, the delaytime difference of the AES and SSL hybrid algorithm is minimum and the encryption is safer, the advantages of low delay, effective access authentication and the like are remarkable, and a better use prospect is brought.

Description

technical field [0001] The invention relates to the field of search management methods, in particular to a search management method for learning big data. Background technique [0002] Learning big data search management is an information management method that obtains encrypted management through searching to avoid information loss during search and affect the search structure of data. However, with the development of science and technology, people have more and more requirements for big data search management methods. The higher it is, the traditional big data search management method can no longer meet people's needs; [0003] Existing big data search management methods have certain disadvantages when used. First, the existing big data search management methods are prone to missing information when searching and downloading plaintext, which affects the correctness and reliability of learning information, and affects information security, and the existing big data files a...

AI Technical Summary

Problems solved by technology

[0002] Learning big data search management is an information management method that obtains encrypted management through searching to avoid information loss during search and affect the search structure of data. However, with the development of science and technology, people have more and more requirements for big data search management methods. The higher it is, the traditional big data search management method can no longer meet people's needs;

[0003] Existing big data search management methods have certain disadvantages when used. First, the existing big data search management methods are prone to missing information when searching and downloading plaintext, which affects the correctness and reliability of learning information, and affects information security, and the existing big data files are usually composed of RSA algorithm and AES algorithm. The end-to-end delay of the existing RSA algorithm is large, and its security and reliability are relatively insufficient; The delay is small, but the encryption security of the algorithm itself is not enough, at the cost of sacrificing security, and the security is reduced. Therefore, we propose a learning big data search management method

Images