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原文：
Intelligent business cloud service platform based on SpringBoot framework
Abstract
This article is based on the SpringBoot platform, which displays real-time news and information on various economies and policies in countries and regions along the 'Belt and Road', and solves the problem of difficult data processing of the 'Belt and Road' complex data. In order to improve the readability of the data, this platform analyzes the cluttered data to generate statistical charts, and obtains key information in real time and intuitively. This system uses Spring, SpringBoot, Mybatis as the background framework scheme, and the front end uses the more popular Vue with strong performance and good performance. Finally, the intelligent cloud service platform system based on B / S architecture is designed, which has practical application value.
Keyword：Belt and Road, Big Data, cloud service, business platform
- INTRODUCTION
A. Research Background
In the course of the “Belt and Road” strategy, various types of massive data will inevitably be generated. How to discover and release hidden and decision-making information from massive, multi-source, and heterogeneous data is particularly important. The role of information mining is mainly to use big data analysis and next-generation artificial intelligence technology to timely and accurately track the progress of the Belt and Road cooperation between China and countries along the route, establish an information resource interconnection mechanism, and provide real-time and predictive information for governments and enterprises Data support and consulting services to make relevant supporting measures and investment cooperation behavior more targeted and scientific.
B. Purpose
In order to solve the problems of the large number of data resources in the “Belt and Road”, such as the fragmentation of the structure, the alienation of the structure, and the difficulty in obtaining knowledge, this paper proposes advanced distributed data collection technologies and distributed search solutions to improve the timeliness and accuracy of early warning of the massive information processing of the “Belt and Road” Based on deep learning to build a knowledge map of the Belt and Road risks and opportunities. Distributed web crawlers have established a multi-source heterogeneous “Belt and Road” information hub, and made breakthroughs in information mining theory and methods.
In view of the diversity of partners in the countries along the Belt and Road, the scope of cooperation, the complexity of data processing, the long-term potential risks and the diversity of risk factors, this project is based on distributed crawler technology and distributed search technology Build a big data center for the “Belt and Road”; build a cloud service for the “Belt and Road” -based information mining based on deep learning and knowledge maps.
C. Research work
Information is the basis of decision-making. How to quickly find the investment opportunities of the “Belt and Road” among the numerous information resources is the most important issue to be solved urgently. Facing such huge and disorderly amounts of information in the countries along the route, and users requirements for the correctness, accuracy, and timeliness of search results, such as the risk assessment of the Sino-US trade war and the historical opportunities of reform and opening up in North Korea, the efficiency and efficiency of information retrieval The rapid response capability of research reports has become an urgent issue. Due to the specific needs of the traditional universal search engines (Google, Baidu, etc.) for the “Belt and Road” theme, there are certain limitations. For example, the results returned by the universal search engine contain a large number of Web pages that “Belt and Road” investors do not care about. Secondly, different data such as pictures, databases, audio, video and multimedia related to the “Belt and Road” appeared in large numbers, and general search engines were often unable to find and obtain these information-intensive and structured data. In addition, most general search engines provide keyword-based retrieval, which is difficult to support queries based on semantic information. Therefore, it is difficult to meet the needs of the “Belt and Road” information retrieval through traditional search tools alone. The use of big data analysis and artificial intelligence technology has become the key to solving the above problems.
This project is based on the big data analysis needs of the “Belt and Road” and leverages the existing big data resources of the “Maritime Silk Road Research Institute” to complete the investment opportunities and risks of the “Belt and Road” cooperation countries through distributed collection and retrieval solutions. Information collection, sorting, storage and integration, based on deep capture and accurate analysis of data resources to create a “Belt and Road” information hub, providing information consulting services and intelligent decision support for Zhejiang enterprises to “go global”.
- KEY TECHNOLOGY
A. System architecture
C / S mode (Client / Server) and B / S mode (Browser / Server) are a mode that work together in current Internet applications. Due to the rise of Web browsers, B / S gradually replaced C / S and was more widely used. With the maturity and popularization of computer network
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