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 effec�tiveness 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 de�sign 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 fu�ture 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 gene�rator and an association rule miner.

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