Telecommunication Companies use data mining techniques to maintain good relationships with their existing customers and attract new customers and identifying profitable/unprofitable customers. Clustering leads to better understanding of customer and its results can be used to definition and decision-making for promotional schemes. In this study, we used the 999-customer purchase records in Sout...

Data can be processed to produce useful information for an organization/company. Example of transaction data that is segment customers. Customer segmentation needs done so sellers find out market conditions and taken into consideration in developing marketing strategies. also make know their customers well. Of course, customer at the Hijabiken Online Store, this store sells Muslim products such...

data mining techniques have been used widely in the area of customer relationship management (crm). in this study, we have applied data mining techniques to address a problem in business-to-business (b2b) setting. in a manufacturer-retailer-consumer chain, a manufacturer should improve its relationship with retailers to continue its business. segmentation is a useful tool for identifying groups...

Data mining techniques have been used widely in the area of customer relationship management (CRM). In this study, we have applied data mining techniques to address a problem in business-to-business (B2B) setting. In a manufacturer-retailer-consumer chain, a manufacturer should improve its relationship with retailers to continue its business. Segmentation is a useful tool for identifying groups...

Deep learning (DL) models have recently been widely used in UAV aerial image semantic segmentation tasks and achieved excellent performance. However, DL are vulnerable to adversarial examples, which bring significant security risks safety-critical systems. Existing research mainly focuses on solving digital attacks for segmentation, but patches with physical attack attributes more threatening t...

This study combines cluster analysis and LRFM (length, recency, frequency, and monetary) model in a pediatric dental clinic in Taiwan to analyze patients' values. A two-stage approach by self-organizing maps and K-means method is applied to segment 1,462 patients into twelve clusters. The average values of L, R, and F excluding monetary covered by national health insurance program are computed ...