Land Subsidence Modelling Using Data Mining Techniques. The Case Study of Western Thessaly, Greece

2018 ◽  
pp. 79-103 ◽  
Author(s):  
Paraskevas Tsangaratos ◽  
Ioanna Ilia ◽  
Constantinos Loupasakis
Keyword(s):  
Data Mining ◽  
Land Subsidence ◽  
Data Mining Techniques ◽  
Using Data

scholarly journals Customers Grouping Using Data Mining Techniques in the Food Distribution Industry (A Case Study)

2020 ◽  
Keyword(s):  
Data Mining ◽  
Customer Segmentation ◽  
Food Distribution ◽  
Data Mining Techniques ◽  
Customer Lifetime ◽  
Rfm Model ◽  
Marketing Activities ◽  
Using Data ◽  
Production Company

Significant data development has required organizations to use a tool to understand the relationships between data and make various appropriate decisions based on the information obtained. Customer segmentation and analysis of their behavior in the manufacturing and distribution industries according to the purposefulness of marketing activities and effective communication and with customers has a particular importance. Customer segmentation using data mining techniques is mainly based on the variables of recency purchase (R), frequency of purchase (F) and monetary value of purchase (M) in RFM model. In this article, using the mentioned variables, twelve customer groups related to the BTB (business to business) of a food production company, are grouped. The grouping in this study is evaluated based on the K-means algorithm and the Davies-Bouldin index. As a result, customer grouping is divided into three groups and, finally the CLV (customer lifetime value) of each cluster is calculated, and appropriate marketing strategies for each cluster have been proposed.

Detection of Desertion Patterns in University Students Using Data Mining Techniques: A Case Study

2018 ◽  
pp. 420-429
Author(s):  
Dayana Vila ◽  
Saúl Cisneros ◽  
Pedro Granda ◽  
Cosme Ortega ◽  
Miguel Posso-Yépez ◽  
...  
Keyword(s):  
Data Mining ◽  
University Students ◽  
Data Mining Techniques ◽  
Using Data

A Case Study on Student Attrition Prediction in Higher Education Using Data Mining Techniques

2019 ◽  
pp. 181-192
Author(s):  
Syaidatus Syahira Ahmad Tarmizi ◽  
Sofianita Mutalib ◽  
Nurzeatul Hamimah Abdul Hamid ◽  
Shuzlina Abdul-Rahman ◽  
Ariff Md Ab Malik
Keyword(s):  
Higher Education ◽  
Data Mining ◽  
Student Attrition ◽  
Data Mining Techniques ◽  
Using Data

Provide a method for validation of bank customers using data mining techniques (Case study: Bank Sepah)

2018 ◽  
Vol 05 (02) ◽  
pp. 145-153
Author(s):  
Fatemeh Sadeghi Laghareh ◽  
Seyed Javad Mirabedini ◽  
Ali Haroon Abadi
Keyword(s):  
Data Mining ◽  
Data Mining Techniques ◽  
Using Data
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