Chinese traditional culture is not only a knowledge, but more importantly, it can shape personality. It can also serve as a way of thinking for the study of practical problems and open the way for innovative thinking.
In the era of big data, data has become another factor of production after labor, capital, land, knowledge, technology and management. With the continuous improvement of the level of informatization, data has been widely used in tax collection and management and tax business. With the help of highly developed information technology and the use of various information systems, it can greatly promote the efficiency of tax management and work quality; Work brings challenges. This paper studies the role of big data in tax collection and management and the improvement of the tax business environment. The research results show that big data tax collection and management has effectively improved the tax business environment: on the one hand, big data tax collection and management can achieve panoramic monitoring of tax sources, combat tax evasion and tax evasion, and significantly improve corporate tax compliance by mastering massive financial and tax data and using big data technology. On the other hand, the big data of tax collection and management reduces taxpayers’ tax costs through online tax collection, and realizes the “policy discoverer” through the intelligent retrieval and push system of preferential tax policies. At the same time, the big data of tax collection and management can reduce the cost of tax declaration through online tax collection, and realize the "policy finder" through the intelligent search and push system of preferential tax policies, so as to improve the execution of preferential tax policies. The research results of this paper provide theoretical support and empirical basis for the continuous improvement of tax informatization construction.
The rapid development of big data technology has transformed the business models of many Chinese enterprises to information. As a new type of production factor, data is gradually being valued by enterprises. Many companies have used big data technology to mine the potential value behind the data, and it has been widely used in the field of financial decision-making. Therefore, it is necessary to introduce big data technology into the financial decision-making process of enterprises, so as to organize and analyze relevant data onto enterprises in a timely and effective manner, so as to provide scientific and effective basis of enterprise decision-makers. This paper mainly adopts literature research method and interdisciplinary research method to deeply study the application process of big data technology in enterprise financial decision-making. This paper first illustrates the necessity of introducing big data technology into the financial decision-making process of enterprises. Then, the main methods and specific functions of big data technology in the process of enterprise financial decision-making to explain the role of big data technology in the process. Finally, the platform of enterprise financial decision-making is designed based on big data technology. This paper finds that the application of big data technology in the financial decision-making process of enterprises is mainly reflected in four aspects: first, data collection; Second, data storage; Third, financial analysis; Fourth, decision support. The introduction of big data technology into the financial decision-making process of enterprises is beneficial to broaden the channels of data collection and enrich the methods of financial analysis and decision-making, but also provides strong support for enterprises to make more accurate and effective financial decision-making schemes.
Today, in the era of big data, data shows the characteristics of large scale, modal diversity and rapid growth. The value of language data also increases explosively, and the value of Chinese corpus information analysis also increases correspondingly. The crawler obtains a large number of Chinese sentences from different styles, establishes a personal corpus, designs and optimizes the database, analyzes the sentence patterns of each corpus in the corpus, and finally establishes a Chinese sentence pattern database, makes full use of a large number of data in the sentence pattern database, and makes multi-directional statistics and analysis of sentence patterns. Taking the corpus in the sentence pattern corpus as a sample, it uses kmeans + + for clustering, The sentence space representation model of the article is constructed, and the feature vector of each article is obtained, so as to carry out the application research of sentence pattern.
Covid-19 has caused a plummet in the number of tourists visiting to the South Central of Vietnam and driven changes in their traveling behaviors. This has formed challenging barriers over the operations of entities in the tourism industry. The purpose of this paper is supporting the tourism organizations to attract domestic and foreign visitors to the South Central of Vietnam post the pandemic. The research uses the secondary data collected by Vitours company - a leading travel agency in South Central - to demonstrate tourists’ demands when visiting destinations in the area between September 2020 and April 2021. Data mining, clustering and association rules techniques are also applied to classify traveler's segmentations and analyze the connections among these groups. The findings of this research indicates 4 clusters of tourists and 6 association rules, which contributes to the stimulus of the tourism industry in South Central after Covid-19.
