A Study on the Logistic Service Satisfaction for Internet Marketing Enterprise Using Data Mining Technology

2011 ◽  
Vol 3 (2) ◽  
pp. 114-120 ◽  
Author(s):  
WenTsao Pan ◽  
PengWen Chen
Keyword(s):  
Data Mining ◽  
Internet Marketing ◽  
Service Satisfaction ◽  
Mining Technology ◽  
Logistic Service ◽  
Using Data

Predicting customer churn in mobile industry using data mining technology

2017 ◽  
Vol 117 (1) ◽  
pp. 90-109 ◽  
Author(s):  
Eui-Bang Lee ◽  
Jinwha Kim ◽  
Sang-Gun Lee
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Online News ◽  
Partial Least Square ◽  
Churn Prediction ◽  
Mining Technology ◽  
Content Type ◽  
Customer Churn ◽  
Mobile Industry ◽  
Using Data

Purpose The purpose of this paper is to identify the influence of the frequency of word exposure on online news based on the availability heuristic concept. So that this is different from most churn prediction studies that focus on subscriber data. Design/methodology/approach This study examined the churn prediction through words presented the previous studies and additionally identified words what churn generate using data mining technology in combination with logistic regression, decision tree graphing, neural network models, and a partial least square (PLS) model. Findings This study found prediction rates similar to those delivered by subscriber data-based analyses. In addition, because previous studies do not clearly suggest the effects of the factors, this study uses decision tree graphing and PLS modeling to identify which words deliver positive or negative influences. Originality/value These findings imply an expansion of churn prediction, advertising effect, and various psychological studies. It also proposes concrete ideas to advance the competitive advantage of companies, which not only helps corporate development, but also improves industry-wide efficiency.

The Application of Data Mining Technology in Mechanical Fault Diagnosis

2011 ◽  
Vol 460-461 ◽  
pp. 821-826
Author(s):  
Yun Feng Lin ◽  
Xiao Ping Hu
Keyword(s):  
Data Mining ◽  
Fault Diagnosis ◽  
Technology Development ◽  
Development Trend ◽  
Advanced Technology ◽  
Mining Technology ◽  
Intelligent Diagnosis ◽  
Hidden Knowledge ◽  
Using Data ◽  
Development Tendency

This article first introduced the survey of mechanical fault diagnosis technology development and the data mining technology theory. Then its application situation at present and the main questions that exist are elaborated. Its development trend is analyzed. The application feasibility of using data mining technology in mechanical fault diagnosis is discussed. Next, the naissance, the development and the future development tendency of data mining technology are introduced. The four algorithms are analyzed and the framework is built too. Intelligent Diagnosis is a major development direction of the fault diagnosis. Knowledge acquisition is the bottleneck of Intelligent Diagnosis development. It comprehensive use of many kinds of advanced technology, discover valuable and hidden knowledge from the large amounts of data mining.

scholarly journals Prediction of Tropical Cyclones’ Characteristic Factors on Hainan Island Using Data Mining Technology

2014 ◽  
Vol 2014 ◽  
pp. 1-13 ◽  
Author(s):  
Ruixu Zhou ◽  
Wensheng Gao ◽  
Bowen Zhang ◽  
Xianggan Fu ◽  
Qinzhu Chen ◽  
...  
Keyword(s):  
Data Mining ◽  
Wind Speed ◽  
Tropical Cyclones ◽  
Statistical Methods ◽  
Average Distance ◽  
Hainan Island ◽  
Mining Technology ◽  
Accurate Judgment ◽  
Combining Data ◽  
Using Data

A new methodology combining data mining technology with statistical methods is proposed for the prediction of tropical cyclones’ characteristic factors which contain latitude, longitude, the lowest center pressure, and wind speed. In the proposed method, the best track datasets in the years 1949~2012 are used for prediction. Using the method, effective criterions are formed to judge whether tropical cyclones land on Hainan Island or not. The highest probability of accurate judgment can reach above 79%. With regard to TCs which are judged to land on Hainan Island, related prediction equations are established to effectively predict their characteristic factors. Results show that the average distance error is improved compared with the National Meteorological Centre of China.

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