This paper conducts in-depth research and analysis on the construction of the public information product APP application platform of urban big media in the context of artificial intelligence and discusses its development. Based on the improvement of the SICAS model, a model of enterprise and user information interaction characteristics in the new media environment is constructed, and social network analysis and semantic analysis methods are used to research enterprise and user information interaction characteristics in the new media environment. The point degree centrality index is used to analyze forwarding and being forwarded behavior in information interaction, the intermediate centrality index is used to analyze following and being followed behavior, the proximity centrality index is used to analyze commenting and being commented behavior, the feature vector centrality index is used to analyze the cohesiveness of information interaction behavior, and the semantic keyword word is used to analyze the semantic keyword word in the research process. The results of the study show that the constructed model can analyze the information interaction behaviors of enterprises and users in the new media environment. The research results show that the constructed model can systematically analyze the information interaction characteristics, and the information interaction between enterprises and users in the new media environment is more timely, more effective, and more satisfying to users. The current situation of the construction of the public information platform and the problems existing in the construction are proposed to achieve the standardization of the construction of the public information platform in the context of smart city, the construction of the platform supervision system, and the strengthening of information security publicity and talent training. To offer a suitable platform and provide efficient solutions for the development of a public information service platform in the city, enhance the professional quality of research papers and dissertations, as well as the solutions’ operability. More public services will be provided in a highly connected way across the boundaries between government, enterprises, society, and citizens and even form a public service market that accepts autonomous choices and becomes an important part of the digital economy, thus finding a good balance between economic development and social welfare.

Determination of the impact of information technology on the field of finance as well as accounting is the main aim of this research. The study in this research paper is based on secondary data analysis; this study was conducted in Pakistan to gather the research data using different websites including world development indicators and used financial reports of health sector companies. Information technology is the main independent variable; it includes scientific practices, business practices, and cultural practices; these are all independent variables. The accounting and finance included return on assets, return on equity, monitory unit policy, revenue remuneration, commercial mortgage, invoice financing, and pension-led funding. These are all considered dependent variables. For measuring the research study, E views software and run different results such as descriptive statistic, cross-covariance, unit root test analysis, and the histogram and state. The result presents that variance ratio analysis of each indicator's overall result found that there are positive and more significant influences of modern information technology on finance and accounting. Therefore, the technology that is playing a vital role in accounting and finance departments is information technology.

With the development of grammar-checking technology and algorithms, the grammar-checking system has been widely used in various fields. This paper designs and implements a grammar-checking system for English composition. The grammar-checking system adopts a multimodule design. The grammar-checking system is composed of a multilayer rule error-correcting module and a machine learning error-correcting module. This study aims to build a machine learning algorithm model that can detect English grammar errors by analysing and comparing different algorithm models currently applied in the field of education and then apply the trained model to the English composition grammar detection system. The results show that the system can save a lot of time and labor cost of manual marking, liberate teachers from heavy and repeated evaluation activities, and put more time and energy on teaching. At the same time, it can provide learners with more objective and timely feedback so that learners can intuitively and clearly know that they are prone to make grammatical mistakes in the process of English learning. It plays a certain assisting and guiding role in English learners’ autonomous learning.

In this paper, machine learning and artificial intelligence are applied to art research to improve the intelligence of art research. This study concludes that the Gaussian homomorphic filter has the best processing impact in the image homomorphic filtering stage by comparing the processing effects of Gaussian homomorphic filter, Butterworth homomorphic filter, and exponential filter. Moreover, this study uses median filtering to eliminate salt and pepper noise in images and designs and implements a rapid digitization system for art works based on three-dimensional reconstruction. In addition, in order to improve the time efficiency of the system and the digital quality of art works and optimize the SIFT feature matching speed, this study proposes a relative position-based SIFT feature fast matching algorithm. Finally, this study verifies the effectiveness of the method proposed in this study through experimental research. The results show that it has a certain effect on promoting the development of art research and the application of computer technology in the art industry.

In order to improve the development effect of private education, this paper analyzes the current situation of private education combined with the data mining algorithm and explores the problems existing in the development of private education. Moreover, this paper combines the semi-parametric product estimation method with parameter estimation and applies the estimation method to model-assisted sampling estimation. This work enhances the estimate accuracy of the sample estimation and increases the field of application of the model while enhancing the classic generalized regression estimation. It also modifies the estimation accuracy on the basis of the linear assumption. The experimental study reveals that the data mining algorithm-based analysis approach for private education development provided in this work has a certain impact, and the development strategy of private education is assessed on this premise.