Market Basket Analysis for E-Commerce using Association Rule Mining

Nowadays, shopping with ecommerce has become the most common lifestyle for everyone in modern era. In order to make the research to be successful, it requires to discover the best research effort to improve the algorithm. In order to make this research successful, author will need to identify the...

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Main Authors: Kayalvily, Tabianan*, Sarasvathi, Nahalingham*, Leong, Kai Cheng*
Format: Article
Language:English
Published: INTI International University 2020
Subjects:
Online Access:http://eprints.intimal.edu.my/1423/
http://eprints.intimal.edu.my/1423/1/ij2020_15.pdf
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author Kayalvily, Tabianan*
Sarasvathi, Nahalingham*
Leong, Kai Cheng*
author_facet Kayalvily, Tabianan*
Sarasvathi, Nahalingham*
Leong, Kai Cheng*
author_sort Kayalvily, Tabianan*
building INTI Institutional Repository
collection Online Access
description Nowadays, shopping with ecommerce has become the most common lifestyle for everyone in modern era. In order to make the research to be successful, it requires to discover the best research effort to improve the algorithm. In order to make this research successful, author will need to identify the best algorithm for finding the item sets frequently bough together and top sales product on each country to predict the sales. The author has developed an ecommerce system which has back-end system to display the performance of the product and using Association Rule Mining on the datasets. By using this system, they can know the hidden product relationships which product has the potential to be purchase together. For develop the system author has uses KDD research methodology which can help to extract the minimal support, confidence and lift from the datasets
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language English
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spelling intimal-14232024-03-18T04:15:36Z http://eprints.intimal.edu.my/1423/ Market Basket Analysis for E-Commerce using Association Rule Mining Kayalvily, Tabianan* Sarasvathi, Nahalingham* Leong, Kai Cheng* QA76 Computer software Nowadays, shopping with ecommerce has become the most common lifestyle for everyone in modern era. In order to make the research to be successful, it requires to discover the best research effort to improve the algorithm. In order to make this research successful, author will need to identify the best algorithm for finding the item sets frequently bough together and top sales product on each country to predict the sales. The author has developed an ecommerce system which has back-end system to display the performance of the product and using Association Rule Mining on the datasets. By using this system, they can know the hidden product relationships which product has the potential to be purchase together. For develop the system author has uses KDD research methodology which can help to extract the minimal support, confidence and lift from the datasets INTI International University 2020-09 Article PeerReviewed text en cc_by_4 http://eprints.intimal.edu.my/1423/1/ij2020_15.pdf Kayalvily, Tabianan* and Sarasvathi, Nahalingham* and Leong, Kai Cheng* (2020) Market Basket Analysis for E-Commerce using Association Rule Mining. INTI JOURNAL, 2020 (15). ISSN e2600-7320 http://intijournal.newinti.edu.my
spellingShingle QA76 Computer software
Kayalvily, Tabianan*
Sarasvathi, Nahalingham*
Leong, Kai Cheng*
Market Basket Analysis for E-Commerce using Association Rule Mining
title Market Basket Analysis for E-Commerce using Association Rule Mining
title_full Market Basket Analysis for E-Commerce using Association Rule Mining
title_fullStr Market Basket Analysis for E-Commerce using Association Rule Mining
title_full_unstemmed Market Basket Analysis for E-Commerce using Association Rule Mining
title_short Market Basket Analysis for E-Commerce using Association Rule Mining
title_sort market basket analysis for e-commerce using association rule mining
topic QA76 Computer software
url http://eprints.intimal.edu.my/1423/
http://eprints.intimal.edu.my/1423/
http://eprints.intimal.edu.my/1423/1/ij2020_15.pdf