The Measurement Research Of Urban Innovation Level Based On Search Engine Data Integration

With the rapid progress of computer technology and the penetration of the Internet in daily life,various electronic devices such as computers,mobile phones,and tablets have become the preferred tools for people to obtain information because of their high real-time performance and wide information range.According to CNNIC survey data,in recent years,the people's demand for and dependence on the Internet has been increasing,and with the comprehensive and in-depth development of science and technology,people also prefer to use the Internet search to obtain and filter the information they need.As the world economy develops more liberalized and market-oriented,competition between different countries and regions is intensifying.In this context,the concept of regional innovation came into being.Regional innovation refers to emphasizing the promotion of own competitiveness from the perspective of innovation in the region,thereby promoting the development of all aspects of society,economy,culture,and life in the region.Therefore,this paper analyzes and studies the provincial innovation level theory,comprehensive evaluation methods,and Internet search engine related literature,and summarizes the shortcomings and deficiencies in these three aspects.It has tentatively proposed the innovation level measurement methods for 31 provinces in China.Based on the measurement results,relevant development countermeasures and suggestions are proposed.The specific work of this article is as follows:(1)Through analyzing the existing problems and shortcomings of the existing urban innovation level measurement index system and comprehensive evaluation methods,and drawing on the science of "Internet+" and "big data" trend,try to apply the data of Internet search engine to the field of comprehensive evaluation,finally determined the urban innovation level measurement index system with 5 main level and 101 secondary index system finally used in this paper.(2)In order to better adapt the Internet search engine data to the measurement of innovation levels in China's provinces,the TF-IDF method was introduced to further improve the fitness and effectiveness of the comprehensive evaluation method.Finally,in order to highlight the real-time nature of Internet data in the time dimension and the dynamic development trend of provincial innovation levels,improved and optimized based on existing dynamic evaluation models with increasing weights in the time dimension of "thin,thick,thin,ancient".In order to solve the problems of different search engines' own information preferences,different cross-platform data scales,and difficulty in assembling,this study introduces the design idea of combined evaluation method to transform the Copeland combination evaluation method into a multidata source comprehensive evaluation method for information aggregation.(3)Based on the evaluation cycle from January 1st to June 24th,2019,data statistics will be conducted 7 days a week for a total of 25 weeks.Taking 31 provinces in China as research objects,the four selected searches will be compared.The engine serves as a data source platform,collects various data of each province in the urban innovation level measurement system,and applies the comprehensive evaluation method proposed in this paper to measure and analyze the urban innovation level of 31 provinces in China.This paper focuses on the evaluation method based on search engine data integration,which can improve the efficiency of comprehensive evaluation and is an important supplement to the traditional statistical data evaluation mode with time lag.The research in this paper is oriented to the level of provincial innovation,which is carried out with an application background.However,because the method itself has high generality,it can also provide method support for similar evaluation problems in other fields.