First, we classify the selected customers into clusters using RFM model to identify high-profit, gold customers. Subsequently, we carry out data mining using association rules algorithm. We measure the similarity, difference and modified difference of mined association rules based on three rules, i.e. Emerging Patten Rule, Unexpected Change Rule, and Added/Perished Rule. In the meantime, we use...

Background: Breast cancer is the second leading cause of cancer death in women, after lung cancer. Due to the importance of predicting this disease, the use of data mining methods in medical research is more significant than before. Data mining algorithms can be a great help in preventing the development of lymphedema in patients. The aim Of this study was to create a diagnosis system that can ...

We propose a data-mining approach for the targeted marketing of new products that have never been rated or purchased by customers. This approach uncovers associations between customer types and product genres that frequently occurred in previous transaction records. Customer types are defined in terms of demographic attribute values that can be aggregated through concept hierarchies; product ty...

At Silicon Graphics, Inc., we have developed a data mining and visualization product called MineSet(Silicon Graphics 1998, Brunk, Kelly & Kohavi 1997). MineSet first released in early 1996 mostly as a visualization product and then became a full data mining and visualization product late that year with several data mining algorithms based onMLC++ (Kohavi, Sommerfield & Dougherty 1997). The engi...

The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer ...

RFM stands for Recency, Frequency and Monetary value. RFM analysis is a marketing technique used for analyzing customer behavior such as how recently a customer has purchased (recency), how often the customer purchases (frequency), and how much the customer spends (monetary). It is a useful method to improve customer segmentation by dividing customers into various groups for future personalizat...

Cardiovascular Disease (CVD) is the foremost cause of death worldwide that generates a high percentage Electronic Health Records (EHRs). Analyzing these complex patterns from EHRs tedious process. To address this problem, Medical Institutions requires effective Predictive Algorithms for Prognosis and Diagnosis Patients. Under work, current state-of-the-art studied to identify leading Algorithms...

Many real world problems deal with ordering objects instead of classifying objects, although majority of research in machine learning and data mining has been focused on the latter. For modeling ordering problems, we generalize the notion of information tables to ordered information tables by adding order relations on attribute values. The problem of mining ordering rules is formulated as findi...