Ranking Association Rules from Data Mining for Health Outcomes: A Case Study of Effect of Industrial Airborne Pollutant Mixtures on Birth Outcomes

2021 ◽  
pp. 633-643
Author(s):  
K. Vu ◽  
A. Osornio-Vargas ◽  
O. Zaïane ◽  
Y. Yuan
Keyword(s):  
Data Mining ◽  
Health Outcomes ◽  
Birth Outcomes ◽  
Association Rules ◽  
Airborne Pollutant ◽  
Pollutant Mixtures

scholarly journals USE OF ASSOCIATION RULES TO PERFORM THE MINING OF A MARKETING DATABASE COMERCIAL

2021 ◽  
Vol 9 (4) ◽  
pp. 142-152
Author(s):  
Priscilla Leão de Lima ◽  
Richardyson Nobrega da Fonseca ◽  
Rilmar Pereira Gomes ◽  
David Barbosa de Alencar
Keyword(s):  
Data Mining ◽  
Association Rules ◽  
Organizational Management ◽  
Apriori Algorithm ◽  
Data Mining Technique ◽  
Mining Technique

Currently, companies seek to find methods to analyze their customer behaviors and profiles. From this, a case study was carried out in a drugstore, in which the data mining technique and the Apriori algorithm were applied, for a better understanding. of your sales. First, a bibliographic survey on data mining and its tasks was carried out. Soon the sales made and their respective products were examined. Finally, marketing standards were presented according to the data analyzed, in order to assist the organizational management and marketing of the examined company.

How Useful Can Be Data Mining For A Continuos Speech Therapist’s Education?

2014 ◽  
Vol 1 (1) ◽  
pp. 339-342
Author(s):  
Mirela Danubianu ◽  
Dragos Mircea Danubianu
Keyword(s):  
Data Mining ◽  
Information And Communication Technology ◽  
Association Rules ◽  
Communication Technology ◽  
Speech Therapy ◽  
Proper Treatment ◽  
Speech Impairments ◽  
Information And Communication ◽  
Specific Education

AbstractSpeech therapy can be viewed as a business in logopaedic area that aims to offer services for correcting language. A proper treatment of speech impairments ensures improved efficiency of therapy, so, in order to do that, a therapist must continuously learn how to adjust its therapy methods to patient's characteristics. Using Information and Communication Technology in this area allowed collecting a lot of data regarding various aspects of treatment. These data can be used for a data mining process in order to find useful and usable patterns and models which help therapists to improve its specific education. Clustering, classification or association rules can provide unexpected information which help to complete therapist's knowledge and to adapt the therapy to patient's needs.

Penerapan Metode Klasifikasi Decision Tree dan Algoritma C4.5 dalam Memprediksi Kriteria Nasabah Kredit Mega Auto Finance

2020 ◽  
Vol 7 (2) ◽  
pp. 200
Author(s):  
Puji Santoso ◽  
Rudy Setiawan
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Microsoft Excel ◽  
Customer Data ◽  
Data Mining Techniques ◽  
C4.5 Algorithm ◽  
Marketing Costs ◽  
Excel Format ◽  
Data Mining Application

One of the tasks in the field of marketing finance is to analyze customer data to find out which customers have the potential to do credit again. The method used to analyze customer data is by classifying all customers who have completed their credit installments into marketing targets, so this method causes high operational marketing costs. Therefore this research was conducted to help solve the above problems by designing a data mining application that serves to predict the criteria of credit customers with the potential to lend (credit) to Mega Auto Finance. The Mega Auto finance Fund Section located in Kotim Regency is a place chosen by researchers as a case study, assuming the Mega Auto finance Fund Section has experienced the same problems as described above. Data mining techniques that are applied to the application built is a classification while the classification method used is the Decision Tree (decision tree). While the algorithm used as a decision tree forming algorithm is the C4.5 Algorithm. The data processed in this study is the installment data of Mega Auto finance loan customers in July 2018 in Microsoft Excel format. The results of this study are an application that can facilitate the Mega Auto finance Funds Section in obtaining credit marketing targets in the future

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