The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Association Rule Mining
Abstract
Association Rule Mining (ARM) is concerned with how items in a transactional database are grouped together. It is commonly known as market basket analysis, because it can be likened to the analysis of items that are frequently put together in a basket by shoppers in a market. From a statistical point of view, it is a semiautomatic technique to discover correlations among a set of variables. ARM is widely used in myriad applications, including recommender systems (Lawrence, Almasi, Kotlyar, Viveros, & Duri, 2001), promotional bundling (Wang, Zhou, & Han, 2002), Customer Relationship Management (CRM) (Elliott, Scionti, & Page, 2003), and cross-selling (Brijs, Swinnen, Vanhoof, & Wets, 1999). In addition, its concepts have also been integrated into other mining tasks, such as Web usage mining (Woon, Ng, & Lim, 2002), clustering (Yiu & Mamoulis, 2003), outlier detection (Woon, Li, Ng, & Lu, 2003), and classification (Dong & Li, 1999), for improved efficiency and effectiveness. CRM benefits greatly from ARM as it helps in the understanding of customer behavior (Elliott et al., 2003). Marketing managers can use association rules of products to develop joint marketing campaigns to acquire new customers. The application of ARM for the cross-selling of supermarket products has been successfully attempted in many cases (Brijs et al., 1999). In one particular study involving the personalization of supermarket product recommendations, ARM has been applied with much success (Lawrence et al., 2001). Together with customer segmentation, ARM helped to increase revenue by 1.8%. In the biology domain, ARM is used to extract novel knowledge on protein-protein interactions (Oyama, Kitano, Satou, & Ito, 2002). It is also successfully applied in gene expression analysis to discover biologically relevant associations between different genes or between different environment conditions (Creighton & Hanash, 2003).
Related Content
Girija Ramdas, Irfan Naufal Umar, Nurullizam Jamiat, Nurul Azni Mhd Alkasirah.
© 2024.
18 pages.
|
Natalia Riapina.
© 2024.
29 pages.
|
Xinyu Chen, Wan Ahmad Jaafar Wan Yahaya.
© 2024.
21 pages.
|
Fatema Ahmed Wali, Zahra Tammam.
© 2024.
24 pages.
|
Su Jiayuan, Zhang Jingru.
© 2024.
26 pages.
|
Pua Shiau Chen.
© 2024.
21 pages.
|
Minh Tung Tran, Thu Trinh Thi, Lan Duong Hoai.
© 2024.
23 pages.
|
|
|