Study On The Optimization Of Slow Travel Space In Tourist Attractions From The Perspective Of Big Data

In recent years,network big data has developed rapidly.It has become a hot topic in the industry and academia.The network trajectory data has the characteristics of large quantity,fast growth and various types.Accompanied by this,the era also urgently needs to use new thinking and methods to make in-depth research on the theory and technology of using and mining large mobile data,so as to better serve the social and economic development.With the rapid development of Internet technology and the popularization of smart phones,mobile APP software and toolkit can process various information conveniently and quickly,and carry out tourism activities independently.Combing and analyzing these massive and multi-type data can provide important information for the healthy development of holiday resorts and accurate analysis of tourist market.It can get rid of the limitations of time,space and types of conventional tourist data collection methods,and also provide new channels for public participation in tourism in the future.The development of tourist resorts is mushrooming,which meets people's increasing demand for leisure and vacation.However,its planning criteria need to be improved.Slow travel space is an important support for tourist resorts.However,most planners plan and layout according to their own experience and ideas,which inevitably leads to appropriate planning results.Based on the current relevant standards and the development requirements of resorts,this paper takes Nanshan tourist resort as a case to plan the spatial layout of tourist roads in the resort area.Based on the research results at home and abroad,this paper analyses the concepts of big data,anti-planning,tourism road system and spatial layout.The establishment of slow space planning and design method of tourist resort not only enriches the theoretical basis of slow space planning of tourist resort,but also provides a more scientific and reasonable method for slow space planning of tourist resort.Enriching the means and methods of systematic research on tourist trails.At present,there are relatively few methods and methods for the study of Tourism Road system.This study takes the combination of large data as the perspective,which greatly enriches the means of tourism slow traffic system.On the basis of field survey,this paper combines the technology of big data analysis in order to depict the slow travel space and its distribution characteristics more comprehensively,scientifically and rigorously,which is helpful to provide decision support for the follow-up design and optimization of the slow travel space.The concept of big data application was adopted earlier,which expanded the field of big data in tourism research.At present,the research of big data in tourism is mostly at the stage of theoretical research,and the practical application is rare.Therefore,this study belongs to the earlier attempt of big data in applied tourism research.