In the era of network information, visualization analysis of data flow is an effective and common means at present. Visualization analysis of data flow is adopted in all walks of life to help solve practical problems. With the continuous development of China's national strength, as the country's main policy to solve rural problems – China countryside has entered a period of vigorous development, many scholars have also produced a lot of achievements in the study of China countryside. This paper mainly relies on the data of CNKI and comprehensively uses the visualization analysis software Cite Spac, TF-IDF algorithm and other methods to carry out visual analysis on the research hotspots of China countryside , in the hope of finding the methods and rules in the construction and development of China countryside to promote the better development of China countryside , and in the hope of advancing the visualization of China countryside research.
{"title":"Research Hotspots and Visual Analysis of Rural China Based on TF-IDF Algorithm","authors":"Jiae Xiang","doi":"10.1145/3598438.3598460","DOIUrl":"https://doi.org/10.1145/3598438.3598460","url":null,"abstract":"In the era of network information, visualization analysis of data flow is an effective and common means at present. Visualization analysis of data flow is adopted in all walks of life to help solve practical problems. With the continuous development of China's national strength, as the country's main policy to solve rural problems – China countryside has entered a period of vigorous development, many scholars have also produced a lot of achievements in the study of China countryside. This paper mainly relies on the data of CNKI and comprehensively uses the visualization analysis software Cite Spac, TF-IDF algorithm and other methods to carry out visual analysis on the research hotspots of China countryside , in the hope of finding the methods and rules in the construction and development of China countryside to promote the better development of China countryside , and in the hope of advancing the visualization of China countryside research.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122023492","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the development of cloud computing, big data, Internet of Things, mobile Internet, artificial intelligence and other new generation information technology, digital payment methods are increasingly widely used. At the same time, the flourishing of major e-commerce platforms has led to huge changes in people's payment methods and consumption levels. In order to study the impact of digital payment on the consumption level and consumption structure of rural residents in Hubei Province, this paper uses panel data of 13 cities and states in Hubei Province from 2013 to 2020, and selects an individual fixed-effects model to conduct an empirical study, which mainly draws the following conclusions: first, digital payment has a significant positive impact on the consumption level of rural residents in Hubei Province; second, the level of digital payment has a significant negative effect on the survival-oriented expenditure, but not on the proportion of hedonic consumption and developmental consumption. This indicates that digital payment can optimize the consumption structure of rural residents in Hubei Province to a limited extent. Finally, corresponding suggestions are made based on the findings of this paper.
{"title":"Study on the Impact of Digital Payment on Consumption of Rural Residents in Hubei Province Based on Panel Data Model","authors":"S. Nie","doi":"10.1145/3598438.3598448","DOIUrl":"https://doi.org/10.1145/3598438.3598448","url":null,"abstract":"With the development of cloud computing, big data, Internet of Things, mobile Internet, artificial intelligence and other new generation information technology, digital payment methods are increasingly widely used. At the same time, the flourishing of major e-commerce platforms has led to huge changes in people's payment methods and consumption levels. In order to study the impact of digital payment on the consumption level and consumption structure of rural residents in Hubei Province, this paper uses panel data of 13 cities and states in Hubei Province from 2013 to 2020, and selects an individual fixed-effects model to conduct an empirical study, which mainly draws the following conclusions: first, digital payment has a significant positive impact on the consumption level of rural residents in Hubei Province; second, the level of digital payment has a significant negative effect on the survival-oriented expenditure, but not on the proportion of hedonic consumption and developmental consumption. This indicates that digital payment can optimize the consumption structure of rural residents in Hubei Province to a limited extent. Finally, corresponding suggestions are made based on the findings of this paper.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126310290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaoyu Du, Changtao Zhang, Zhijie Han, Guanying Zhou
With the application of Internet of things technology, smart home is gradually changing people's lifestyle. However, IoT devices are vulnerable to attacks that leak user privacy, it leads to some security issues. In this paper, a BFP authentication scheme combining fog computing and blockchain technology is proposed, and the Paillier encryption algorithm is used to generate the key, which ensures the security and privacy of data. Finally, we compare the encryption and decryption efficiency of Paillier and RSA encryption algorithms, and evaluate and analyze them from several aspects. The results show that the proposed scheme has superior performance in terms of security, and the computational overheads of key execution is less than the traditional scheme. Under the premise of ensuring data security, the proposed scheme can effectively improve the execution efficiency of IoT devices.
{"title":"Security authentication scheme of smart home based on BFP","authors":"Xiaoyu Du, Changtao Zhang, Zhijie Han, Guanying Zhou","doi":"10.1145/3598438.3598451","DOIUrl":"https://doi.org/10.1145/3598438.3598451","url":null,"abstract":"With the application of Internet of things technology, smart home is gradually changing people's lifestyle. However, IoT devices are vulnerable to attacks that leak user privacy, it leads to some security issues. In this paper, a BFP authentication scheme combining fog computing and blockchain technology is proposed, and the Paillier encryption algorithm is used to generate the key, which ensures the security and privacy of data. Finally, we compare the encryption and decryption efficiency of Paillier and RSA encryption algorithms, and evaluate and analyze them from several aspects. The results show that the proposed scheme has superior performance in terms of security, and the computational overheads of key execution is less than the traditional scheme. Under the premise of ensuring data security, the proposed scheme can effectively improve the execution efficiency of IoT devices.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121689418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper selects the panel data of 22 listed tourism companies from 2007 to 2020 as the research sample, uses the random frontier analysis to calculate the operating efficiency of listed tourism companies, and analyzes the relationship between the economic growth target and the multiple regression model and the threshold effect model of the listed tourism companies. The study found that: (1) the economic growth target has a significant positive impact on the operating efficiency of listed tourism companies.(2) The operating efficiency of state-owned enterprises is more promoted by the economic growth targets, while non-state-owned enterprises are smaller.(3) Financing constraints have a threshold effect in the relationship between the economic growth target and the operating efficiency of listed tourism companies. When the financing constraints exceed a certain threshold value, the promotion effect of the economic growth target on the operating efficiency of listed tourism companies will be significantly reduced.
{"title":"Research on Economic Growth Target and Operating Efficiency of Listed Tourism Companies based on Multiple Regression Model and Threshold Effect Model","authors":"Lei Peng, Peng Hongli, Gabriel Xiao-Guang Yue","doi":"10.1145/3598438.3598450","DOIUrl":"https://doi.org/10.1145/3598438.3598450","url":null,"abstract":"This paper selects the panel data of 22 listed tourism companies from 2007 to 2020 as the research sample, uses the random frontier analysis to calculate the operating efficiency of listed tourism companies, and analyzes the relationship between the economic growth target and the multiple regression model and the threshold effect model of the listed tourism companies. The study found that: (1) the economic growth target has a significant positive impact on the operating efficiency of listed tourism companies.(2) The operating efficiency of state-owned enterprises is more promoted by the economic growth targets, while non-state-owned enterprises are smaller.(3) Financing constraints have a threshold effect in the relationship between the economic growth target and the operating efficiency of listed tourism companies. When the financing constraints exceed a certain threshold value, the promotion effect of the economic growth target on the operating efficiency of listed tourism companies will be significantly reduced.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134513315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the current competitive communication industry, how to avoid user churn has become an important issue for enterprises. The development of big data technology has provided a new way for communication companies to predict subscriber churn. This paper predicts user churn based on 900,000 data from QD Mobile using a dataset processed by random sampling. The accuracy of three algorithms, including decision tree, random forest and AdaBoost classifier, is compared for user churn prediction. The random forest algorithm is found to be the most accurate for user churn prediction. Based on this, grid search algorithm in machine learning is used to find the best parameters of the random forest model and improve the prediction accuracy to 81.84%. The result can help communication companies to predict subscriber churn probability and improve competition level.
{"title":"Research on User Churn Warning based on Machine Learning","authors":"Zhou Yiran, Wang Lei, Liu Wei, Xiao Tao","doi":"10.1145/3598438.3598461","DOIUrl":"https://doi.org/10.1145/3598438.3598461","url":null,"abstract":"In the current competitive communication industry, how to avoid user churn has become an important issue for enterprises. The development of big data technology has provided a new way for communication companies to predict subscriber churn. This paper predicts user churn based on 900,000 data from QD Mobile using a dataset processed by random sampling. The accuracy of three algorithms, including decision tree, random forest and AdaBoost classifier, is compared for user churn prediction. The random forest algorithm is found to be the most accurate for user churn prediction. Based on this, grid search algorithm in machine learning is used to find the best parameters of the random forest model and improve the prediction accuracy to 81.84%. The result can help communication companies to predict subscriber churn probability and improve competition level.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123179889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Collaborative optimization and deep integration are the key tasks of the current college education reform. It is difficult to quantitatively analyze the fusion process and the advantages and disadvantages of the methods. This paper adopts the gray fuzzy theoretical model, combines the fuzzy mathematics theory and the gray system theory, and conducts quantitative analysis on the vague qualitative indicators, so as to obtain more reliable analysis results.
{"title":"Analysis and Research on the Related Modes of Collaborative Optimization and Deep Fusion Based on Grey Fuzzy Theory","authors":"Huang Fashuang, Fang Fang","doi":"10.1145/3598438.3598458","DOIUrl":"https://doi.org/10.1145/3598438.3598458","url":null,"abstract":"Collaborative optimization and deep integration are the key tasks of the current college education reform. It is difficult to quantitatively analyze the fusion process and the advantages and disadvantages of the methods. This paper adopts the gray fuzzy theoretical model, combines the fuzzy mathematics theory and the gray system theory, and conducts quantitative analysis on the vague qualitative indicators, so as to obtain more reliable analysis results.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130484831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shengze Qin, Jialei Guo, Haimanot B Atinkut, Chongjun Yang
Based on the China Household Tracking Survey 4-period tracking data from 2012-2018, this paper measures the poverty vulnerability of Chinese farm households using the VEP method, and then constructs driving variables as proxy variables for precise poverty alleviation policies, measures their policy effects using fuzzy breakpoint regression, and tests the continuity and breakpoint regression validity of the driving variables, and finds that (1) in terms of time, the incidence of poverty vulnerability among Chinese farm households shows an overall decreasing trend except for a small increase in 2016, and by 2018, there are still 10.11% of farm households located in a state of vulnerability under the $1.3 poverty line; under different poverty lines, the average poverty vulnerability index shows a decreasing trend in recent years. (2) In terms of regional dimensions, the poverty vulnerability of Chinese farm households is highest in the west, followed by the central region, and lowest in the east. Compared with the east and central regions, rural residents in the west are more likely to fall into poverty in the future, and there are large differences in the depth of poverty in different regions. (3) The fuzzy breakpoint regression model found that the poverty alleviation policy significantly reduced the poverty vulnerability of rural households, and the regression results passed the continuity test of the driving variables and the breakpoint regression validity test.
{"title":"The Impact of Precise Poverty Alleviation Policies on the Vulnerability of Farm Households to Poverty: Research Based on Micro Big Data","authors":"Shengze Qin, Jialei Guo, Haimanot B Atinkut, Chongjun Yang","doi":"10.1145/3598438.3598441","DOIUrl":"https://doi.org/10.1145/3598438.3598441","url":null,"abstract":"Based on the China Household Tracking Survey 4-period tracking data from 2012-2018, this paper measures the poverty vulnerability of Chinese farm households using the VEP method, and then constructs driving variables as proxy variables for precise poverty alleviation policies, measures their policy effects using fuzzy breakpoint regression, and tests the continuity and breakpoint regression validity of the driving variables, and finds that (1) in terms of time, the incidence of poverty vulnerability among Chinese farm households shows an overall decreasing trend except for a small increase in 2016, and by 2018, there are still 10.11% of farm households located in a state of vulnerability under the $1.3 poverty line; under different poverty lines, the average poverty vulnerability index shows a decreasing trend in recent years. (2) In terms of regional dimensions, the poverty vulnerability of Chinese farm households is highest in the west, followed by the central region, and lowest in the east. Compared with the east and central regions, rural residents in the west are more likely to fall into poverty in the future, and there are large differences in the depth of poverty in different regions. (3) The fuzzy breakpoint regression model found that the poverty alleviation policy significantly reduced the poverty vulnerability of rural households, and the regression results passed the continuity test of the driving variables and the breakpoint regression validity test.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126903406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Under the background that Chinese governments at all levels promote the integrated development of culture and tourism, this paper applies the coupled coordination degree model, By processing the data of the number of museums, public libraries, mass art galleries, art performing groups, gymnasiums, A-level scenic spots and above, travel agencies, star-rated hotels, inbound tourists, domestic tourists, foreign exchange income from tourism and domestic tourism income, etc., This paper analyzes the tourism development level, cultural development level and coupling coordination degree of cities and prefectures in Hubei province, and puts forward countermeasures to strengthen the deep integration of culture and tourism industry in Hubei province.
{"title":"The level measurement of cultural and tourism integration of tourism cities in Hubei Province based on coupling coordination degree","authors":"Hong Xue, Xiuli Wang, Xuerui Xu, Lily Zhang","doi":"10.1145/3598438.3598447","DOIUrl":"https://doi.org/10.1145/3598438.3598447","url":null,"abstract":"Under the background that Chinese governments at all levels promote the integrated development of culture and tourism, this paper applies the coupled coordination degree model, By processing the data of the number of museums, public libraries, mass art galleries, art performing groups, gymnasiums, A-level scenic spots and above, travel agencies, star-rated hotels, inbound tourists, domestic tourists, foreign exchange income from tourism and domestic tourism income, etc., This paper analyzes the tourism development level, cultural development level and coupling coordination degree of cities and prefectures in Hubei province, and puts forward countermeasures to strengthen the deep integration of culture and tourism industry in Hubei province.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115242188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tourism is an important part of the service industry. This paper takes a certain tourist attraction as the guide to conduct a comprehensive analysis of the relevant local tourism industry clusters, especially for in-depth discussions on the competitiveness of tourism industry clusters. Based on the GEM model Above all, combined with the factor analysis method to find out the main factors affecting the development of the tourism industry, put forward corresponding countermeasures, provide reference for the coordinated development of the regional tourism industry, and realize the quantitative analysis of the competition behavior of industrial clusters, which has practical significance for the development of the tourism industry.
{"title":"Research on Tourism Resource Development Model Based on GEM","authors":"Xue Bingwang, Lei Peng, Gabriel Xiao-Guang Yue","doi":"10.1145/3598438.3598456","DOIUrl":"https://doi.org/10.1145/3598438.3598456","url":null,"abstract":"Tourism is an important part of the service industry. This paper takes a certain tourist attraction as the guide to conduct a comprehensive analysis of the relevant local tourism industry clusters, especially for in-depth discussions on the competitiveness of tourism industry clusters. Based on the GEM model Above all, combined with the factor analysis method to find out the main factors affecting the development of the tourism industry, put forward corresponding countermeasures, provide reference for the coordinated development of the regional tourism industry, and realize the quantitative analysis of the competition behavior of industrial clusters, which has practical significance for the development of the tourism industry.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"234 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123736687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In recent years, listed companies in general have poor risk management, the proportion of listed companies affected by the Chinese financial crisis is growing, resulting in a large number of bad debts. Thus, it is worthwhile to establish an early warning system for listed companies' financial crisis before it occurs, and to inform managers and investors in advance, so that effective measures can be implemented as soon as possible to eliminate the crisis's hidden dangers. In this paper, 181 ST enterprises from Shanghai and Shenzhen are chosen, and 181 non-ST enterprises from Shanghai and Shenzhen are matched 1:1, and a financial risk early-warning model based on principal component analysis and logistic regression is built. After obtaining 15 financial indicators through DuPont analysis, 8 financial indicators are chosen as early-warning indicators based on their significance, and a model for predicting financial crises is established through logistic regression analysis. According to the results, the logistic prediction model is superior.
{"title":"Based on Panel Logistic model about Early warning of financial distress of listed companies in automobile industry","authors":"Wan Xiaodan","doi":"10.1145/3598438.3598462","DOIUrl":"https://doi.org/10.1145/3598438.3598462","url":null,"abstract":"In recent years, listed companies in general have poor risk management, the proportion of listed companies affected by the Chinese financial crisis is growing, resulting in a large number of bad debts. Thus, it is worthwhile to establish an early warning system for listed companies' financial crisis before it occurs, and to inform managers and investors in advance, so that effective measures can be implemented as soon as possible to eliminate the crisis's hidden dangers. In this paper, 181 ST enterprises from Shanghai and Shenzhen are chosen, and 181 non-ST enterprises from Shanghai and Shenzhen are matched 1:1, and a financial risk early-warning model based on principal component analysis and logistic regression is built. After obtaining 15 financial indicators through DuPont analysis, 8 financial indicators are chosen as early-warning indicators based on their significance, and a model for predicting financial crises is established through logistic regression analysis. According to the results, the logistic prediction model is superior.","PeriodicalId":338722,"journal":{"name":"Proceedings of the 2022 3rd International Symposium on Big Data and Artificial Intelligence","volume":"185 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124749216","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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