Enterprise-level full-amount data intelligent search implementation method and system

Abstract

The invention provides an enterprise-level full-amount data intelligent search implementation method and system. The system comprises an access layer, a model layer, an algorithm layer, a component layer, a service layer and a display layer, and the design of the system follows four unified principles, namely, a unified leader, a unified plan, a unified standard and a unified construction principle. Exemplary application construction should fully consider safety protection, fault-tolerant capability and anti-interference capability of the system, ensure long-term stable, safe, reliable and efficient operation of the system, have good compatibility and expansibility, abide by the design concept of taking customers as the center, provide consistent and user-friendly experience, meet the actual needs of services to the maximum extent, and the operation is convenient, the functions are complete and the interface is friendly; the application design adopts an international advanced technicalroute. Old and heterogeneous compatible technologies are fully utilized, and previous IT investment of state grid companies is protected. The system and the method meet the international and nationaluniversal standard and support various hardware platforms are supported.

Description

technical field [0001] The invention relates to the field of information technology, in particular to a method and system for realizing intelligent search of enterprise-level full data. Background technique [0002] With the rapid development of cloud computing, big data, Internet of Things, mobile applications and other information technologies, the company has carried out a lot of research and applications, bringing new opportunities for the transformation of enterprise production methods and management models. During the "13th Five-Year Plan" period, the company's business will be upgraded from focusing on supporting business operations to comprehensively assisting analysis and decision-making. It is necessary to strengthen the comprehensive analysis and mining of cross-business data, strengthen the analysis of semi-structured and unstructured data, and build more Multi-regular and self-learning data analysis requires the information system to provide the ability to store...

AI Technical Summary

Problems solved by technology

[0011] Existing search engines only allow a group of keywords and logical operators to form questions, but keyword retrieval cannot fully meet user requirements, and it is a blind match, and natural language understanding is a very difficult task. still under study

[0012] 4) Cannot retrieve historical information with

This table may contain thousands of connection pointers pointing to Web sites, and users may only select a small part and discard the rest, because users cannot have such patience, and as a result, they may lose a lot of useful information

[0016] 6) Limitation of a single engine

In addition, it is reported that major commercial search engines receive 15,000 to 20,000 questions per minute, which puts a lot of pressure on index servers

[0018] 7) Difficult to provide users with effective personalized services

[0019] Since different users have different interests and hobbies, the required retrieval results should also be targeted. However, the existing search engines cannot provide effective personalized services for a single user, which greatly increases the time for users to query useful information.

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