Title :
Targeting customers with data mining techniques: Classification
Author :
Shahrokhi, Nazanin ; Dehzad, Roxana ; Sahami, Soheila
Author_Institution :
Dept. of Inf. Technol. Manage., Azad Univ., Tehran, Iran
fDate :
Nov. 29 2011-Dec. 1 2011
Abstract :
The valuable knowledge can be discovered through data mining process for further use and prediction. There are different data mining techniques, such as clustering, association, and classification. Classification is one of the major techniques to discover the patterns in huge amounts of data. This technique is widely used in various fields. However, it has not attracted enough attention in marketing concepts. This article presents a study on targeting customers with a data mining approach, considering their past performance. Using this approach, the performance patterns can be discovered from an existing data set of the San Francisco airport, including the information of its passengers. Furthermore, we identify the limitations of current work and raise several directions forfuture research.
Keywords :
data mining; pattern classification; pattern clustering; travel industry; San Francisco airport; association; classification; clustering; customer targeting; data mining techniques; passenger information; pattern discovery; classification; data mining; targeting customers;
Conference_Titel :
User Science and Engineering (i-USEr), 2011 International Conference on
Conference_Location :
Shah Alam, Selangor
Print_ISBN :
978-1-4577-1654-6
DOI :
10.1109/iUSEr.2011.6150567