The Method Of Interest Text Recommendation In English Education Based On Data Mining

2022 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Linlin  Fan
Keyword(s):  
Data Mining ◽  
English Education

scholarly journals Analysis of Students’ Behavior in English Online Education Based on Data Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Chunxia Wang
Keyword(s):  
Data Mining ◽  
Online Education ◽  
Prediction Error ◽  
Student Behavior ◽  
English Education ◽  
Learning System ◽  
Processing Efficiency ◽  
High Data ◽  
Fuzzy Neural ◽  
Continuous Application

With the formation of global economic integration for better exchange and cooperation with nations around the world, mastering English is extremely essential. In the context of today’s big era with a variety of English learning methods, it is required that data mining be applied to online English education. Owing to the continuous application of data mining techniques and the improvement of the online learning system, its application in education is also more and more prevalent. In the face of a large amount of learning data and student behavior data, the traditional methods have the problems of low processing efficiency, more memory requirements, and large prediction error. Therefore, this paper proposes a student behavior analysis method of online English education based on data mining. The student behavior data is collected, and an online English education learning behavior model is established. The data mining model is built to filter the obtained behavior data through data preparation, data statistics, and analysis. Furthermore, the apriori algorithm is used to mine association rules and calculate the similarity of data followed by the application of a fuzzy neural network to mine the behavior data of English online education students. The experimental results show that this method has high data processing efficiency, takes up less space, and produces a low prediction error.

scholarly journals Cloud Classroom Design for English Education Based on Internet of Things and Data Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Xiaohua Luo
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Social Life ◽  
English Education ◽  
Teaching Method ◽  
College Teaching ◽  
Test Analysis ◽  
Teaching Resources ◽  
Development Platform ◽  
English Classroom

The Informa ionization of social life and the globalization of economy have made the importance of English increasingly prominent. Building an information-based teaching platform for supplementary teaching under the network environment has become a mainstream teaching method in various basic schools. How to integrate various types of multimedia teaching resources into English classroom teaching has become the main goal of the current college teaching reform. Aiming at the shortcomings of the current English education classroom, this paper designs and develops an English education cloud classroom based on the Internet of Things and data mining methods. First of all, the system adopts a three-tier B/S model, the development platform chooses, NET, the development language, uses ASP.NET, and the database chooses SQL server. Secondly, the data mining method is used to clean and organize the data in the cloud classroom background to explore the course education status behind the data. Finally, the simulation test analysis verifies the efficiency of the English education cloud classroom established in this article.

Data Mining and Machine Learning

2020 ◽  
Author(s):  
Mohammed J. Zaki ◽  
Wagner Meira, Jr
Keyword(s):  
Machine Learning ◽  
Data Mining

Heart Rate Variability, Emotions, and Music

2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce
Keyword(s):  
Data Mining ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Vegetative State ◽  
Low Frequency ◽  
Emotional Reactions ◽  
Heart Beat ◽  
Healthy Controls ◽  
Frequency Spectra ◽  
Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

Post, Mine, and Be Disturbed: Social Media Data Mining

PsycCRITIQUES ◽  
2016 ◽  
Vol 61 (51) ◽  
Author(s):  
Daniel Keyes
Keyword(s):  
Data Mining ◽  
Social Media ◽  
Social Media Data ◽  
Media Data

English Education Observational Measure

2019 ◽  
Author(s):  
Lisset V. Toro ◽  
Eliana I. Pinza ◽  
Alba B. Vargas ◽  
Alexandra Zúñiga ◽  
Fabian M. Paredes ◽  
...  
Keyword(s):  
English Education ◽  
Observational Measure
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