Framework and performance analysis of college English testing system based on data mining technology

2021 ◽  
pp. 1-11
Author(s):  
Liu Narengerile ◽  
Li Di ◽  
Keyword(s):  
Data Mining ◽  
Test System ◽  
Test Time ◽  
Testing System ◽  
Test Results ◽  
System Software ◽  
Examination System ◽  
Mining Technology ◽  
College English ◽  
And Performance

At present, the college English testing system has become an indispensable system in many universities. However, the English test system is not highly humanized due to problems such as unreasonable framework structure. This paper combines data mining technology to build a college English test framework. The college English test system software based on data mining mainly realizes the computer program to automatically generate test papers, set the test time to automatically judge the test takers’ test results, and give out results on the spot. The test takers log in to complete the test through the test system software. The examination system software solves the functions of printing test papers, arranging invigilation classrooms, invigilating teachers, invigilating process, collecting test papers, scoring and analyzing test papers in traditional examinations. Finally, this paper analyzes the performance of this paper through experimental research. The research results show that the system constructed in this paper has certain practical effects.

Data mining artificial intelligence technology for college english test framework and performance analysis system

2020 ◽  
pp. 1-11
Author(s):  
Lin Shen
Keyword(s):  
Data Mining ◽  
Performance Analysis ◽  
Evaluation Model ◽  
Diagnostic Evaluation ◽  
Test Paper ◽  
Test Question ◽  
College English ◽  
Question Recommendation ◽  
And Performance ◽  
Analysis System

This article first studies and designs the college English test framework and performance analysis system. The author analyzes a large number of data collected by the system in three dimensions: using data mining title association models, using machine learning to merge college English score prediction models, and finally diagnosing on the basis of the sexual evaluation model, the author designed and implemented a test paper algorithm based on the association rules of the question type, and carried out relevant verification from the three aspects of test paper time, test question recommendation and improvement according to scores. Finally, according to the needs analysis, the author uses the diagnostic evaluation model and related test paper algorithm to design and implement the diagnostic evaluation model, which is added to the college English diagnostic practice system. It can be obtained through comparative experiments that the paper-based algorithm based on the diagnostic evaluation model proposed in this paper can effectively give better practice guidance and test question recommendation to the learner’s learning status and knowledge point problem obstacles, and can effectively improve learning. The achievements of the authors have broad application prospects and research value.

Design of College English Process Evaluation System Based on Data Mining Technology and Internet of Things

2020 ◽  
Vol 16 (2) ◽  
pp. 18-33 ◽  
Author(s):  
Hongli Lou
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Process Evaluation ◽  
Evaluation System ◽  
Current Situation ◽  
The Internet ◽  
Mining Technology ◽  
College English ◽  
Procedural Evaluation ◽  
The Internet Of Things

This article proposes a new idea for the current situation of procedural evaluation of college English based on Internet of Things. The Internet of Things is used to obtain the intelligent data to enhance the teaching flexibility. The data generated during the process of procedural evaluation is carefully analyzed through data mining to infer whether the teacher's procedural evaluation in English teaching can be satisfied.

scholarly journals Study on Low-Frequency TEM Effect of Coal during Dynamic Rupture

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Cheng-wu Li ◽  
Chuan Wang ◽  
Bei-jing Xie ◽  
Xiao-yuan Sun ◽  
Xiao-meng Xu
Keyword(s):  
High Strain ◽  
Low Frequency ◽  
Test System ◽  
Test Results ◽  
Dynamic Rupture ◽  
Monitoring Technique ◽  
Shpb Test ◽  
Coal Rock ◽  
And Performance ◽  
Electromagnetic Monitoring

Dynamic loads provided by the SHPB test system were applied to coal specimens, and the TEM signals that emerged during coal rupture were recorded by the TMVT system. Experiments on coal-mass blasting rupture in excavating workface were also carried out, and the emerged TEM signal was analyzed. The results indicate that the low-frequency TEM signals were detected close to the coal specimens under high strain dynamic load applied by the SHPB, initially rising sharply and dropping rapidly, followed by a small tailing turbulence. And the field test results obtained during coal blasting process coincided with the results from the SHPB tests. Furthermore, its initial part shaped like a pulse cluster had a more pronounced tail and lasted even longer. And the generation mechanism of the low-frequency TEM effect was analyzed. It suggests that the low-frequency TEM effect of coal during dynamic rupture is contributed by the fractoemission mechanism and the resonance or waveguide effects. Because its wavelength is longer than the higher ones, the low-frequency TEM has a good anti-interference performance. That can expand the scope and performance of the coal-rock dynamic disaster electromagnetic monitoring technique.

scholarly journals Application of Data Mining Technology Based on Data Center

2022 ◽  
Vol 2146 (1) ◽  
pp. 012017
Author(s):  
Longjun Zhang ◽  
Kun Liu ◽  
Ilyar Ilham ◽  
Jiaxin Fan
Keyword(s):  
Data Mining ◽  
Computer Science ◽  
Data Center ◽  
Rapid Development ◽  
Research Field ◽  
The Internet ◽  
Test Results ◽  
Mining Technology ◽  
Processing Data ◽  
Definition Of

Abstract Data mining technology refers to the use of mathematics, statistics, computer science and other methods to process a large amount of information to obtain useful conclusions and provide valuable decisions for people. With the rapid development and popularization of the Internet era and the more and more extensive application of computers in various fields, data mining technology has become a hot research field in today’s society. Based on the data center, this paper studies the data mining technology. Firstly, this paper expounds the definition of data mining, and studies the process of data mining and the steps of processing data. Then, this paper also designs and studies the framework of data mining, and tests the performance of the algorithm. Finally, the test results show that data mining technology can well meet the target requirements.

scholarly journals Fault Prediction Method Based on Data Mining in Semiconductor Test Line

2011 ◽  
Vol 2-3 ◽  
pp. 706-710
Author(s):  
Ren Hong Yue ◽  
Yu Min Ma ◽  
Fei Qiao ◽  
Xing Hao Wu
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Test Line ◽  
Prediction Method ◽  
Test System ◽  
Fault Prediction ◽  
Test Time ◽  
Mining Method ◽  
Semiconductor Test ◽  
Time Point

In semiconductor test system, test equipment all have a period of usage. When the test time of equipment is larger than its period of usage, its fault will occur frequently. This paper will use data mining method to predict the next time point of fault based on the history data related to equipment fault. By this, a method of equipment fault prediction will be put forward, and provide the decision support for semiconductor equipment maintenance.

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