Market Basket Analysis for E-Commerce using Association Rule Mining

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


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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

Item Type: Article
Uncontrolled Keywords: Market Basket Analysis, E-Commerce, KDD methodology
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Information Technology
Depositing User: Unnamed user with email
Date Deposited: 28 Sep 2020 06:34
Last Modified: 28 Sep 2020 06:34

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