Network Teaching Technology Based on Big Data Mining and Information Fusion

Du, Yishan; Zhao, Tianzhong

doi:10.1155/2021/6629563

Cited by 27 publications

(22 citation statements)

References 19 publications

(17 reference statements)

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“…Generally speaking, the body of recommendation policy-targeted resolution usually includes historical data of users, semantic content, and association between items. The basic idea of collaborative filtering methods commonly used in the field of recommendation systems is to make interest prediction or demand prediction by looking for similar users' preferences or items other than the target users [23]. User rating information for items is the most common information used in collaborative filtering recommendations.…”

Section: Classification and Comparison Of Recommendationmentioning

confidence: 99%

Research on Data Mining Algorithm of Associated User Network Based on Multi-Information Fusion

Kang

Hua

2022

Journal of Sensors

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In order to explore how to realize network mining for associated users, an algorithm of associated user mining based on recommendation system is proposed. This method recommends key technical problems and solutions based on multi-information fusion to explore the research of user network data mining. The data mining algorithm of associated user network based on multi-information fusion is about 35% higher than the previous method. This article is combined with common scoring data to improve the accuracy of algorithm results. The experiment was carried out on the real data set FilmTrust to evaluate the proposed new algorithm, measure the prediction accuracy of the score prediction results, and compare the offline test results to verify the effectiveness of the new algorithm.

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Section: Classification and Comparison Of Recommendationmentioning

confidence: 99%

Research on Data Mining Algorithm of Associated User Network Based on Multi-Information Fusion

Kang

Hua

2022

Journal of Sensors

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“…For the purpose of meeting the needs of knowledge-based society and constructing an education system of lifelong education and learning, China has envisioned the development of distance education using the advantageous resources of general schools since early years [1]. Modern IT represented by networking, digitalization, multimedia, and intelligence has become the main tool to expand people's ability and quality [2]. It has changed people's traditional way of living, learning, and working and has brought a profound impact on modern education content and teaching methods, which has also triggered a boom in the integration of IT and curriculum [3].…”

Section: Introductionmentioning

confidence: 99%

Integration and Recommendation of Multimedia Network-Assisted English Instructional Resources Based on Association Rules Mining

Liu¹

2022

Mobile Information Systems

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The integration of multimedia teaching refers to a novel teaching mode that combines multimedia, information resources, and information methods with content and teaching process in the teaching process with the guidance of contemporary educational ideas and organically unifies them on a spatial and temporal platform, so as to better accomplish the teaching tasks. However, with the deepening of network teaching and school connotation construction, various resources such as media materials, courseware, network courses, and teaching cases generated by education and teaching, as well as academic works, papers, patents, project results, and lectures of experts and professors gathered by scientific research, are increasing. In this situation, how to integrate teaching resources and courses to provide students with an independent learning platform and an information-based learning environment has become an urgent issue. For this problem, data mining has shown a strong vitality, and data mining can find out the potential connection between datasets. Association rule mining is the most researched and widely used data mining method. In this paper, we propose a multimedia network-assisted English integration of educational resources method based on association rule algorithm to give full play to the role of “multimedia technology” and realize the integration of traditional English teaching and information network culture, so as to achieve the purpose of optimizing English teaching. The experimental results show that with the increase of data volume, the average testing time of Apriori is reduced by 56.49 s compared with MapReduce, so the advantage of Apriori algorithm is more obvious. Therefore, this research can effectively provide students with rich and colorful personalized resources, realize high-performance interactive learning, and help students cultivate their independent learning ability as well as their lifelong learning habits.

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“…Suppose J is the full name of n items, J = fi 1 , i 2 , ::i n :g. Transaction T ∈ J, item level X ∈ J. There are two basic criteria for measuring association rules, as follows [28]:…”

Section: Association Rules Based On Data Miningmentioning

confidence: 99%

Enterprise Decision-Making and Analysis Based on E-Commerce Data Mining

Wang

Huang

2022

Wireless Communications and Mobile Computing

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Enterprises have established a number of business processing systems and business websites according to their own characteristics and business needs, such as e-commerce websites and shopping websites. Over time, a large number of sales transaction data and customer purchase information have been generated, but no useful information has been generated stored in the database. Therefore, the management and decision-making levels of enterprises try to get useful information from huge and complex data. With the development of network technology and database, data mining technology has emerged. Nowadays, data mining technology has become one of the most concerned technologies of e-commerce. It can select appropriate data mining methods according to the characteristics of commodities, carry out effective statistical analysis and decision support for data, predict and analyze future market trends, greatly improve the business intelligence analysis of e-commerce enterprises, and make enterprises have greater advantages in market competition. This paper explains some important methods related to data mining and designs a data mining system. One of the systems can help e-commerce decision-makers analyze and predict data. Through experiments, it is concluded that the average absolute percentage errors of prediction data are 8.6% and 5.3%, respectively, with small errors and high accuracy. Second, make better recommendations for users. After investigation and analysis, the highest satisfaction has increased by 25% after using the system.

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Network Teaching Technology Based on Big Data Mining and Information Fusion

Cited by 27 publications

References 19 publications

Research on Data Mining Algorithm of Associated User Network Based on Multi-Information Fusion

Research on Data Mining Algorithm of Associated User Network Based on Multi-Information Fusion

Integration and Recommendation of Multimedia Network-Assisted English Instructional Resources Based on Association Rules Mining

Enterprise Decision-Making and Analysis Based on E-Commerce Data Mining

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