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Research on Construction of a Cloud Platform for Tourism Information Intelligent Service Based on Blockchain Technology
Wireless Communications and Mobile Computing Pub Date : 2020-10-28 , DOI: 10.1155/2020/8877625
Cao Wei 1 , Qinan Wang 1 , Chengying Liu 1
Affiliation  

The development of global tourism has put forward new requirements for the construction of smart tourism. More and more travel-related data have reached the level of TB or even PB, which has brought great difficulties to tourism management. This article explores the use of big data technologies such as genetic algorithms to explore massive travel data and establish a comprehensive tourism information service platform for governments, enterprises, tourists, and scientific research institutions. The overall design of an industrial information service platform based on big tourist data is proposed. The overall function, data source, data standard, and application scope of the platform are all focused on. The traceability and nontampering of blockchain technology can also help passengers retain and verify their identity information. From the perspective of the design goals of the system, in general, the time required for repeated authentication will greatly reduce air ticket bookings, accommodation reservations, and bill verification, and improving efficiency is the only way to establish a “trust ecology.” Architecture design, distributed architecture, and intelligent service design, as well as the key implementation technology of service platform construction, route recommendation algorithm and tourism information big data mining, research and analysis on the construction of tourism information intelligent service.

中文翻译:

基于区块链技术的旅游信息智能服务云平台建设研究

全球旅游业的发展对智能旅游建设提出了新的要求。越来越多的与旅行有关的数据达到了结核病甚至PB的水平,这给旅游管理带来了很大的困难。本文探索了利用遗传算法等大数据技术来探索海量旅行数据,并为政府,企业,游客和科研机构建立一个综合的旅游信息服务平台。提出了基于大游客数据的工业信息服务平台的总体设计。平台的整体功能,数据源,数据标准和应用范围都在关注上。区块链技术的可追溯性和不可篡改性还可以帮助乘客保留和验证其身份信息。从系统设计目标的角度来看,通常,重复身份验证所需的时间将大大减少机票预订,住宿预订和账单验证,而提高效率是建立“信任生态”的唯一途径。架构设计,分布式架构和智能服务设计,以及服务平台建设,路线推荐算法和旅游信息大数据挖掘的关键实现技术,对旅游信息智能服务建设的研究与分析。
更新日期:2020-10-30
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