Research on Data Mining Technology of Social Network Associated Information

2018 ◽  
pp. 17-26
Author(s):  
Yanxin Jiang ◽  
Xian Mei ◽  
Guanglu Sun
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Mining Technology

Research and Prototype Implementation of Network Group Sentiment Analysis Based on Topic

2014 ◽  
Vol 1042 ◽  
pp. 218-223
Author(s):  
Ya Hao He ◽  
Ya Ru Yang ◽  
Yu Zhong Qian ◽  
Jing Li
Keyword(s):  
Data Mining ◽  
Social Network ◽  
Sentiment Analysis ◽  
Group Structure ◽  
Complex Relationship ◽  
Mining Technology ◽  
Prototype Implementation ◽  
The Social

In the era of Web2.0, people in the social network make up a complex relationship called group by communicating with others, such as forward or comment. Such networks are typically abundant with valuable information which can be mined. We use data mining technology to analyze the network group structure based on different topics, divide the network group into multiple sub-communities, analyze sentimenttendency of different communities, views and frequentpatterns, and present the overall characteristics of whole group visually to the users to help them make decisions.

Advanced Statistical Tools for Improving Yield and Reliability

1999 ◽  
Author(s):  
Richard C. Kittler
Keyword(s):  
Data Mining ◽  
Analysis Data ◽  
Neural Nets ◽  
Future Trends ◽  
Statistical Tools ◽  
Mining Technology ◽  
Explanatory Variables ◽  
Data Coverage ◽  
Statistical Approaches ◽  
Adequate Data

Abstract Analysis of manufacturing data as a tool for failure analysts often meets with roadblocks due to the complex non-linear behaviors of the relationships between failure rates and explanatory variables drawn from process history. The current work describes how the use of a comprehensive engineering database and data mining technology over-comes some of these difficulties and enables new classes of problems to be solved. The characteristics of the database design necessary for adequate data coverage and unit traceability are discussed. Data mining technology is explained and contrasted with traditional statistical approaches as well as those of expert systems, neural nets, and signature analysis. Data mining is applied to a number of common problem scenarios. Finally, future trends in data mining technology relevant to failure analysis are discussed.

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.

scholarly journals Mechanical equipment fault detection applying data mining technology

2020 ◽  
Vol 1684 ◽  
pp. 012024
Author(s):  
Yiqun Liu ◽  
Xiaogang Wang ◽  
Xiaoyuan Gong ◽  
Hua Mu
Keyword(s):  
Data Mining ◽  
Fault Detection ◽  
Mechanical Equipment ◽  
Mining Technology
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