A Knowledge Image Construction Method for Effective Information Filtering and Mining From Education Big Data

Xie, Yunfang; Wen, Peng; Hou, Wenhui; Liu, Yingdi

doi:10.1109/access.2021.3074383

Cited by 5 publications

(2 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In other grade calculation methods, the location of specific grades provides assessment information for the teacher department [ 23 ]. Xie et al used the principles of determining cost-sensitive classification learning and balancing costs to create an objective function with the goal of minimizing costs [ 24 ]. Cai and Wu introduced the classical association rule Apriori algorithm and the well-known decision tree algorithm ID3 and used the association rule algorithm to find out the effect of excellence in one course on another course [ 25 ].…”

Section: Related Workmentioning

confidence: 99%

Design of Repository and Search Platform for Art Painting Teaching Resources in Universities Based on Model of Decision Tree

Liu

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

At present, art education curriculum reform is in full swing. Art education in China started late but as an important element of quality education. Art education is particularly important today with rapid economic development and advanced technology. The art subject is the sum of the teaching content of the art subject and the execution of teaching activities expressed through the network, including two components: the teaching content organized according to specific teaching objectives and teaching strategies and the network teaching support environment. Unlike existing multimedia courseware, several features reflect the advantages of online education, unlike online courseware. Each school generates a large amount of student performance data every year, and existing systems only perform simple backups, queries, and statistics on these data, which do not reflect the weaknesses of education in a centralized and comprehensive manner. Data mining can extract valuable information hidden behind the data from a large amount of data and has been applied in more and more fields with good results, which helps people to make correct decisions. In this study, we propose a decision tree model-based repository and search platform for school art and painting education resources, briefly outline the decision tree model, and analyze the architecture and operation of the school art and painting education resources repository and search platform. The experimental results show that the Virginica accuracy of the decision tree model is 0.42 higher than that of C4.5, which greatly improves the accuracy of the preferred class and ensures the overall accuracy remains unchanged. Therefore, this system realizes the art education resource repository system and realizes the needs of college users to share art professional information and resources.

show abstract

Section: Related Workmentioning

confidence: 99%

Design of Repository and Search Platform for Art Painting Teaching Resources in Universities Based on Model of Decision Tree

Liu

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…e proposed method reduces time and energy consumption in the execution process. Xie et al [17] proposed an information filtering and mining method for big data analysis. A support vector machine (SVM) algorithm is used here to analyze the data necessary for the mining process.…”

Section: Related Workmentioning

confidence: 99%

Data Management and Service Mode of Library Based on Data Mining Algorithm

Zhang

Chi

2022

Scientific Programming

View full text Add to dashboard Cite

Data management for large-scale data library services with mining procedures improves the availability and readiness of heterogeneous sources. The heterogeneous data sources are assimilated as a single entity through mining procedures to meet the data demands. This article introduces connectivity-persistent data mining method (CDMM) to improve the data handling precision with boosting availability. The proposed method relies on federated learning for identifying the service demands, thereby providing data mining. The learning paradigm accumulates information on shared data library existence over various services. Based on the availability, further mining demands are forwarded to the data management system. If the existence verified by the federated learning is adaptable, then sharing-enabled mining is endorsed for the connected users. The data management then augments several heterogeneous shared libraries to meet the mining requirements. This process is reversible based on the service mode and existence. Therefore, the proposed method improves data availability with less mining and access time and fewer failures.

show abstract

Data Association Mining Method of Vocational College Students’ Employment Education Based on Machine Learning Model

Zhou

2024

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

View full text Add to dashboard Cite

A Knowledge Image Construction Method for Effective Information Filtering and Mining From Education Big Data

Cited by 5 publications

References 28 publications

Design of Repository and Search Platform for Art Painting Teaching Resources in Universities Based on Model of Decision Tree

Design of Repository and Search Platform for Art Painting Teaching Resources in Universities Based on Model of Decision Tree

Data Management and Service Mode of Library Based on Data Mining Algorithm

Data Association Mining Method of Vocational College Students’ Employment Education Based on Machine Learning Model

Contact Info

Product

Resources

About