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With the rise of "Internet+" as a national strategy, traditional industries have accelerated their integration with the Internet, and the education industry has also begun to seek innovative development. The fast-paced life of modern people makes time for learning more fragmented, and the high pressure of life makes people want to avoid excessive pressure from learning. These give opportunities and advantages to the development of online education, which is more adaptable to fragmentation and light weight. Online learning effectively solves the drawbacks of imbalance between supply and demand of offline education by solving the problems of time, distance, capacity, and scarcity of educational resources. In this paper, we take H International Education Group as the research subject. The paper combines the practice of precise English teaching theory and big data technology analysis tools to study the optimization of English teaching strategies in the K12 English training product market of H International Education Group. The materials prevalent in the English vocabulary market today are "one-size-fits-all," presenting the same vocabulary resources to all learners without taking into account the differences in learning styles, learning preferences, and original cognitive structures of different learners. [ABSTRACT FROM AUTHOR]

In digital marketing, the core advantages of scientific and technological means such as artificial intelligence and big data analysis gradually appear and pay attention to them. This paper studies the accuracy of digital marketing and proposes an intelligent algorithm based on data analysis, which improves the effect of marketing communication. Through the combination of intelligent algorithms and big data analysis, the data are convincing. Through the comparison and improvement of intelligent algorithm logistic regression and XGBoost, this paper puts forward an improved algorithm of XGBoost based on Bayesian optimization parameters, which can improve the efficiency of digital marketing communication and enhance the social influence of digital marketing. [ABSTRACT FROM AUTHOR]

Language is a symbol reflecting ideas and is an important medium for people to realize information transfer and communication. Culture is all the material and spiritual wealth created during the historical development of human society. Language and culture are inseparable. When we learn a language, we must also understand the cultural content it contains. Learning English requires an understanding of the culture of British and American countries, and thus teachers must necessarily teach culture in the English classroom. At present, the software and hardware of Internet technology in our country have been developed in-depth, and the total amount of big data has been in the trend of growth, and China has officially entered the era of big data. This paper takes the reform of teaching mode of British and American culture courses as the main research object and explores how to build a diversified and blended teaching mode based on the existing teaching mode and integrating various online teaching resources under the premise of various technologies in the background of "big data." In order to accelerate the integration and optimization of such course resources, promote the development of theoretical teaching and practical teaching of such courses and improve students' professional ability. [ABSTRACT FROM AUTHOR]

With the growing development of the era of big data, data acquisition and analysis have become hot spots, and Python-based crawler technology is one of the most widely used tools in data analysis work at present. In this paper, we apply Python crawler key technology to acquire data of movie list and hot movies on Cat's Eye movie network, analyze data based on Python development environment Spyder, use the Numpy system to store and process large data, Chinese Jieba word separation tool to crawl data for word separation text processing, Snownlp library to process text sentiment, and finally by the word cloud map and web dynamic map display information such as viewers' emotional tendency and movie rating statistics, and provide decision support for users' movie viewing. [ABSTRACT FROM AUTHOR]

Plant variety rights are essential for agricultural development and food security. This paper mainly starts with the cost-benefit issue of plant variety rights that enterprises are concerned about, and introduces the cost-benefit analysis method into the research and development, application, and protection of plant variety rights. This research takes the new plant variety rights as the research object, clarifies the development status of the world plant variety rights from the perspective of time series development characteristics and spatial distribution pattern, explores the location of the variety rights in the world, and uses methods such as knowledge measurement and data mining, to carry out in-depth research on the application and authorization of plant variety rights, the scope of protection catalogues, the structure of variety rights, and the applicant unit. Finally, the regression model is tested from five aspects: regression model significance test, model goodness-of-fit test, Hosmer goodness-of-fit test, goodness-of-fit test, and overall accuracy test of model prediction. The regression coefficient of plant variety rights cooperation in the research process was 1.908, and the statistical test value was significant at the 5% level (P = 0.022 < 0.05). Using system dynamics to evaluate its risks, it provides new ideas for the risk analysis and prevention of seed industry enterprises' variety rights capitalization operation. [ABSTRACT FROM AUTHOR]

With the development of information technology, the era of big data has gradually entered classroom teaching, and the evaluation of students' learning quality and classroom teaching efficiency has been widely concerned. In order to further improve the quality of classroom teaching in colleges and universities, this paper analyzes the classroom teaching quality evaluation and feedback system based on the big data. Principal component analysis is used to analyze the evaluation index of classroom teaching quality and feedback information to apartment. Through the study of education quality estimate and feedback system under big data, the feedback mechanism of classroom teaching quality evaluation is improved to achieve high-quality and efficient teaching. [ABSTRACT FROM AUTHOR]

This paper adopts "digital landscape design logic," analyzes and researches smart city and digital landscape design, and builds a digital city based on design logic, design basis, environment analysis, and results in a presentation based on the dilemma of landscape garden planning and design at this stage and the development trend of the smart garden and digital landscape design. The optimization model of the landscape and environment design is constructed based on design logic, design basis, environment analysis, and result presentation. First, on the Hadoop distributed computing platform based on the MapReduce parallel processing framework, we implement the massive small file processing methods (Hadoop Archives, CombineFileInputFormat, and Sequence Files) to compensate for the inherent defects of Hadoop and experimentally compare the memory consumption and execution efficiency of the three methods to propose a choice. The memory consumption and execution efficiency of the three methods are experimentally compared to propose a selection strategy. Finally, based on the MR-PFP algorithm, we parallelize the frequent itemset in-cab trajectory big data to generate interesting strong association rules. The experimental results show that the MR-PFP algorithm has better speedup ratio performance and higher mining efficiency than the parallel frequent pattern (PFP) growth algorithm. The research and analysis focused on the digital implementation of the standalone environmental analysis, using Rhino software and Grasshopper visual programming language to build parametric logic, establish parametric analysis models, and conduct a comprehensive analysis of the current environment. The study explores the use of digital landscape design methods and technologies in the landscape design process. Using Rhino + Grasshopper parametric and visualization programming software, we built parametric analysis models around elevation, slope, slope direction, water catchment, and viewable area and used mapping and overlay techniques to quantify the urban space. Finally, the purpose of collecting, monitoring, analyzing, simulating, creating, and reproducing landscape information is achieved. [ABSTRACT FROM AUTHOR]

The explosion in the number of Internet of Things (IoT) devices simply reflects how the growth of big data overlaps perfectly with the growth of the Internet of Things. With the advent of the era of big data, the continuous development of our country's economy, and the continuous progress of society, the development of social work is also influenced by economic and social development and continues to go hand in hand, making corresponding contributions to the development of our country's society. Meanwhile, the gradual imbalance between social development and economic development has put much pressure on social work organizations. The research on the social work development model has aroused the concern and discussion of some experts and scholars in recent years. In our paper, we aim to analyze the characteristics of social work models, the role of social work institutions, and the problems of social work models and combine them with qualitative research and quantitative research to make the questionnaire survey method. The results of the survey show that the effective percentages of "satisfaction" and "very satisfied" for "your enthusiasm for work" and "sense of accomplishment that your work brings you" are 68.0% and 58.7%, respectively. It can be seen from this that social workers have a strong sense of experience in the overall work when performing specific tasks. [ABSTRACT FROM AUTHOR]

In the big data environment, the visualization technique has been increasingly adopted to mine the data on library and information (L&I), with the diversification of data sources and the growth of data volume. The previous research into the information association of L&I visualization network rarely tries to construct such a network or explore the information association of the network. To overcome these defects, this paper explores the visualization of L&I from the perspective of big data analysis and fusion. Firstly, the authors analyzed the topology of the L&I visualization network and calculated the metrics for the construction of L&I visualization topology map. Next, the importance of meta-paths of the L&I visualization network was calculated. Finally, a complex big data L&I visualization network was established, and the associations between information nodes were analyzed in detail. Experimental results verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]