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Detecting Customer Purchasing Patterns using Association Rule Mining

Paradkar, Rhutujit Uday (2022) Detecting Customer Purchasing Patterns using Association Rule Mining. Masters thesis, Dublin, National College of Ireland.

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The market basket analysis plays a very important role in driving the business of any organization especially in retail domain. Performing market basket analysis helps the business owners to get a better idea about the different purchasing patterns of the customers. The recommendation systems make use of association rules on a very large scale to find association between the products so that they can be often bought together. The research in this paper mainly focuses on the market basket analysis in the retail sector. The datasets that are selected for the experiments are from a retail shop, a bakery and a online retail shop in UK.The association rule mining algorithms that are used in this paper are apriori, FP-growth and theEclat algorithms. The aim of this experiment is to apply the algorithms to each dataset selected and then use clustering algorithm like the k-means to reduce the size of the dataset by clustering together different association rules. The time and performance of each of the algorithm on the dataset is recorded for comparison. In this experiment the market basket analysis was performed on the datasets along with the K means clustering to reduce the size of the datasets and also principal component analysis was done to reduce the dimensionality of the dataset.

Item Type: Thesis (Masters)
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
H Social Sciences > HF Commerce > Marketing > Consumer Behaviour
H Social Sciences > HF Commerce > Electronic Commerce
Divisions: School of Computing > Master of Science in Data Analytics
Depositing User: Tamara Malone
Date Deposited: 27 Feb 2023 16:24
Last Modified: 27 Feb 2023 16:24

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