Market basket analysis with association rules in the retail sector using Orange. Case Study: Appliances Sales Company
This research is conducted to analyze the shopping basket by using association rules in the retail area, more specically in a home goods sales company such as appliances, computer items, furniture, and sporting goods, among others. With the rise of globalization and the advancement of technology, re...
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| Format: | Article |
| Language: | English |
| Published: |
Centro Latinoamericano de Estudios en Informática
2021-07-01
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| Series: | CLEI Electronic Journal |
| Subjects: | |
| Online Access: | http://www.clei.org/cleiej/index.php/cleiej/article/view/497 |
| _version_ | 1818892242577784832 |
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| author | Garcia-Diaz Maria-Elena Marcos Martinez Bel´en Escobar Bel´en Escobar Diego P. Pinto-Roa |
| author_facet | Garcia-Diaz Maria-Elena Marcos Martinez Bel´en Escobar Bel´en Escobar Diego P. Pinto-Roa |
| author_sort | Garcia-Diaz Maria-Elena |
| collection | DOAJ |
| description | This research is conducted to analyze the shopping basket by using association rules in
the retail area, more specically in a home goods sales company such as appliances, computer
items, furniture, and sporting goods, among others. With the rise of globalization
and the advancement of technology, retail companies are constantly struggling to maintain
and raise their prots, as well ordering the products and services that the customer
wants to obtain. In this sense, they need a new approach to identify different objectives
in order to be more competitive and successful, looking for new decision-making
strategies. To achieve this goal, and to obtain clear and efficient strategies, by providing
large amounts of data collected in business transactions, the need arises to intelligently
analyze such data in order to extract useful knowledge that will support decision-making
and, an understanding of the association patterns that occur in sales-customer behavior.
Predicting which product will make the most prot, products that are sold together, this
type of information is of great value for storing products in inventory. Knowing when a
product is out of fashion can support inventory management effectively. In this sense,
this work presents the rules of association of products obtained by analyzing the data
with the FPGrowth algorithm using the Orange tool. |
| first_indexed | 2024-12-19T17:53:36Z |
| format | Article |
| id | doaj.art-c0988784439b43539b91e0fe30c71d49 |
| institution | Directory Open Access Journal |
| issn | 0717-5000 |
| language | English |
| last_indexed | 2024-12-19T17:53:36Z |
| publishDate | 2021-07-01 |
| publisher | Centro Latinoamericano de Estudios en Informática |
| record_format | Article |
| series | CLEI Electronic Journal |
| spelling | doaj.art-c0988784439b43539b91e0fe30c71d492022-12-21T20:11:52ZengCentro Latinoamericano de Estudios en InformáticaCLEI Electronic Journal0717-50002021-07-0124210.19153/cleiej.24.2.12Market basket analysis with association rules in the retail sector using Orange. Case Study: Appliances Sales CompanyGarcia-Diaz Maria-Elena0Marcos MartinezBel´en Escobar Bel´en Escobar Diego P. Pinto-RoaUniversidad Nacional de AsunciónThis research is conducted to analyze the shopping basket by using association rules in the retail area, more specically in a home goods sales company such as appliances, computer items, furniture, and sporting goods, among others. With the rise of globalization and the advancement of technology, retail companies are constantly struggling to maintain and raise their prots, as well ordering the products and services that the customer wants to obtain. In this sense, they need a new approach to identify different objectives in order to be more competitive and successful, looking for new decision-making strategies. To achieve this goal, and to obtain clear and efficient strategies, by providing large amounts of data collected in business transactions, the need arises to intelligently analyze such data in order to extract useful knowledge that will support decision-making and, an understanding of the association patterns that occur in sales-customer behavior. Predicting which product will make the most prot, products that are sold together, this type of information is of great value for storing products in inventory. Knowing when a product is out of fashion can support inventory management effectively. In this sense, this work presents the rules of association of products obtained by analyzing the data with the FPGrowth algorithm using the Orange tool.http://www.clei.org/cleiej/index.php/cleiej/article/view/497Knowledge Discovery in DatabasesData MiningMarket Basket AnalysisAssociation RulesOrange CanvasFP- Growth |
| spellingShingle | Garcia-Diaz Maria-Elena Marcos Martinez Bel´en Escobar Bel´en Escobar Diego P. Pinto-Roa Market basket analysis with association rules in the retail sector using Orange. Case Study: Appliances Sales Company CLEI Electronic Journal Knowledge Discovery in Databases Data Mining Market Basket Analysis Association Rules Orange Canvas FP- Growth |
| title | Market basket analysis with association rules in the retail sector using Orange. Case Study: Appliances Sales Company |
| title_full | Market basket analysis with association rules in the retail sector using Orange. Case Study: Appliances Sales Company |
| title_fullStr | Market basket analysis with association rules in the retail sector using Orange. Case Study: Appliances Sales Company |
| title_full_unstemmed | Market basket analysis with association rules in the retail sector using Orange. Case Study: Appliances Sales Company |
| title_short | Market basket analysis with association rules in the retail sector using Orange. Case Study: Appliances Sales Company |
| title_sort | market basket analysis with association rules in the retail sector using orange case study appliances sales company |
| topic | Knowledge Discovery in Databases Data Mining Market Basket Analysis Association Rules Orange Canvas FP- Growth |
| url | http://www.clei.org/cleiej/index.php/cleiej/article/view/497 |
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