Application Research on Marketing Data Analysis Using Data Mining Technology

2016 ◽  
Author(s):  
Xiaoyan Wang
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Application Research ◽  
Mining Technology ◽  
Marketing Data ◽  
Using Data

The Application of Data Mining Technology in the Data Analysis of Traditional Chinese Medicine

2014 ◽  
Vol 687-691 ◽  
pp. 1266-1269
Author(s):  
Zhen Wang ◽  
Kan Kan She
Keyword(s):  
Data Mining ◽  
Information Technology ◽  
Data Analysis ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Rapid Development ◽  
Theoretical Knowledge ◽  
Mining Technology ◽  
Mining Methods ◽  
Using Data

With the rapid development of information technology, the amount of data accumulated by people is increasing sharply. Data mining technology is an effective method to find useful information from vast amounts of data and increase the utilization of information. After thousands of years of development, traditional Chinese medicine has accumulated a wealth of theoretical knowledge and a lot of books and records, more and more Chinese medicine databases are created. Using data mining technology to mine the unknown knowledge and rules and put forward assumptions for experiment and theory can be a good auxiliary research of traditional Chinese medicine. This article analyzes the data mining methods of traditional Chinese medicine at first. Then, the application of data mining technology in traditional Chinese medicine data analysis is introduced which includes the data mining of traditional Chinese medicine literatures, diagnosis and clinic of traditional Chinese medicine and prescription and medication of traditional Chinese medicine. At last, the aspects which need to be paid attention to in the data mining of traditional Chinese medicine are pointed out.

scholarly journals Analyze and Enhance Sales in Lulu Supermarket using Data Mining Technology

2020 ◽  
Author(s):  
Ahmed Abdullah Awadh Koofan ◽  
Mohammed Kaleem
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Association Rules ◽  
Association Rule ◽  
Relevant Information ◽  
Research Association ◽  
Mining Technology ◽  
Time Consumption ◽  
Huge Data ◽  
Using Data

-Data mining is a powerful technology for analyzing huge data, it has many techniques such as; classification, clustering, prediction and association rules etc., In this research Association rule will be used for analyzing data, which will help to extract the data related to combinations of items. Numerous customers tends to purchase items regularly, each time they visit supermarket, customer’s need to move around from shelf to shelf for the product of their interest which is time consuming. This research will help to minimize the time consumption for customers by analyzing the customer’s invoices and letting know the supermarket about the patterns of customer's orientations. In this work python tool will be used for data mining, by using association rule to analyze the customer’s purchases and retrieve the relevant information which will help to determine the customer’s pattern and know the association between products. In this rationale, the data of customer’s purchases were collected from Lulu hypermarket for data analysis and the outcomes of the analysis is to know the customer’s patterns and making the shopping easy by reorganizing the related items and the most buying items together on same shelf.

K-MEANS CLUSTERING ALGORITHM FOR SERVICE DATA ANALYSIS BASED ON CUSTOMERS COMBINATION

2018 ◽  
Vol 3 (1) ◽  
pp. 001
Author(s):  
Zulhendra Zulhendra ◽  
Gunadi Widi Nurcahyo ◽  
Julius Santony
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Clustering Algorithm ◽  
Customer Complaints ◽  
Using Data ◽  
Clustering Data ◽  
Service Data ◽  
Selection Of

In this study using Data Mining, namely K-Means Clustering. Data Mining can be used in searching for a large enough data analysis that aims to enable Indocomputer to know and classify service data based on customer complaints using Weka Software. In this study using the algorithm K-Means Clustering to predict or classify complaints about hardware damage on Payakumbuh Indocomputer. And can find out the data of Laptop brands most do service on Indocomputer Payakumbuh as one of the recommendations to consumers for the selection of Laptops.

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.

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