Data Mining for Retail Website Design and Enhanced Marketing

Data mining is considered as one of the most powerful technologies that participates greatly in helping companies in any industry to focus on the most important information in their data warehouses. In this book, we developed a new approach that measures the effectiveness of data mining in helping retail websites designers to improve the structure of their websites during the design phase. This approach overcomes web usage mining drawbacks, improves the website design structure, and reduces maintenance efforts needed in the future.We studied the behavior of items with respect to time. We showed how association rule mining can be invested to improve the process of decision making in a retail business through exploring current and previous product buying behavior and predicting and controlling future trends and behaviors. Based on our idea that interesting frequent itemsets are mainly covered by many recent transactions, a new method to mine for interesting frequent itemsets is introduced. Finally, we introduced the TARtool which is a temporal dataset generator and an association rule miner.

Asem Omari obtained his PhD degree from the Institute of Computer Science at Heinrich-Heine University Duesseldorf, Germany in 2008. He obtained the Graduate Certificate in Computer and Information Sciences from the University of Michigan, Dearborn, USA in 2002. He completed his Bachelor degree in Applied Mathematics from Jordan University of Science and Technology, Jordan in 1999. Since 2005 he has been researching in data and web mining and their applications in web design and marketing.