customers segmentation and analyzing their behavior at fast moving costumer goods (fmgs) industries which deal with a large number of customers with a variety of characteristics causes the marketing activities to be targeted and leads to effective communication with the customers. segmentation, a data mining approach, which leads to the discovery of similar groups of customers, is usually done ...

Retained fetal membranes (RFM) is a frequent postpartum disorder in cattle causing considerable economic losses, and common indication for antibiotic (AB) administration. There controversy with regard to the treatment of RFM, scientific recommendations are often conflict current legislation on AB use practical routines field. The aim this study was assess therapeutic approaches RFM by Belgian r...

Rockfall causes a large number of accidents and fatalities in steep environments. A realistic quantification rockfall risk is thus crucial for an effective prevention damages loss lives. The estimation block volumes different return periods thereby remains major challenge. In this paper, we present straightforward frequency model (RFM: Frequency Model) its application at 8 sites 7 locations the...

Organizations use data mining to improve their customer relationship management processes. Data mining is a new and well-known technique, which can be used to extract hidden knowledge and information about customers’ behaviors. In this paper, a model is proposed to enhance the premium calculation policies in an automobile insurance company. This method is based on customer clustering. K-means a...

Data mining methodology has a tremendous contribution for extracting the hidden knowledge and patterns from the existing databases. Traditionally, researchers use basket data to mine association rules of which the basic task is to find the frequent items. For relational databases whose data format is relational data other than basket data, RDB-MINER algorithm was proposed. In this paper, we int...

Almost all the papers on market segmentation modeling using retail transaction data reported in the literatures deal with finding groupings of customers. This paper proposes the application of clustering techniques on finding groupings of retailers who use the Electronic Funds Transfer at Point Of Sale (EFTPOS) facilities of a major bank in Australia in their businesses. The RFM (Recency, Frequ...

Data mining has a tremendous contribution for researchers to extract the hidden knowledge and information which have been inherited in the raw data. This study has proposed a brand new and practical fuzzy analytic network process (FANP) based weighted RFM (Recency, Frequency, Monetary value) model for application in K-means algorithm for auto insurance customers’ segmentation. The developed met...

This paper proposes a new weighted mining frequent pattern based on customer’s RFM(Recency, Frequency, Monetary) score for personalized u-commerce recommendation system under ubiquitous computing. An existing recommendation system using traditional mining has the problem, such as delay of processing speed from a cause of frequent scanning a large data, considering equal weight value of every it...