Knowledge discovery in databases: development of analytic tools for the e-commerce sector using java

Schindler, Jonas (2015) Knowledge discovery in databases: development of analytic tools for the e-commerce sector using java. [Dissertation (University of Nottingham only)]

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Today businesses of the e-commerce sector collect huge amounts of data as apart of their daily business operations. This data contains valuable information in the form of hidden knowledge. In order to harvest this knowledge businesses need to make use of data mining applications that support them in analysing and interpreting the data.

The objective of this dissertation is to develop and evaluate an application that has the potential of supporting businesses of the e-commerce industry.

At the beginning general concepts that are related to the subject are introduced. These are data mining, including business intelligence, data warehousing and Knowledge Discovery in Databases (KDD). More specifically applied concepts from the e-commerce industry are presented as well. The Market Basket Analysis is a very famous example for the practical use of data mining in the e-commerce sector. It is used to identify products that are frequently bought together.

An application is developed to provide basic data mining and analytic functionality to small and medium sized businesses of the e-commerce industry. The software serves as the backend of an e-commerce shopping application, which was developed prior to this project. The back end accesses data produced by the shopping front end and offers multiple ways of analysing this data. Among them is the functionality to carry out a Market Basket Analysis. Moreover, basic product and customer data management tools are included in the application as well.

The software is developed with the programming language Java and makes use of the GUI framework JavaFX. The e-commerce and Analytics data is stored in a MySQL database. The connection between the java application and the database is established with the database API, JDBC.

Item Type: Dissertation (University of Nottingham only)
Depositing User: Gonzalez-Orbegoso, Mrs Carolina
Date Deposited: 09 Dec 2015 15:33
Last Modified: 30 Dec 2017 13:03

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