Data Mining for Retail Website Design and Enhanced Marketing : Techniques and Applications

Asem Omari

ISBN 10: 3639064844 / ISBN 13: 9783639064841

Editore: VDM Verlag Dr. Müller, VDM Verlag Dr. Müller E.K., 2008

Riguardo questo articolo

Neuware - 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.

Codice articolo 9783639064841

Dati bibliografici

• Titolo: Data Mining for Retail Website Design and Enhanced Marketing : Techniques and Applications
• Editore: VDM Verlag Dr. Müller, VDM Verlag Dr. Müller E.K.
• Data di pubblicazione: 2008
• Lingua: Inglese
• ISBN 10: 3639064844
• ISBN 13: 9783639064841
• Rilegatura: Taschenbuch
• Condizione: Neu

Descrizione articolo

Riassunto

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.