We  deal with the relationship termination problem in the context of individual-level customer relationship management (CRM) and use a Markov decision process to determine the most appropriate occasion for termination of the relationship with a seemingly unprofitable customer. As a particular case, the beta-geometric/beta-binomial model is considered as the basis to define customer beha...

Correctly and effectively customer classification according to their characteristics and behaviors will be the most important resource for electronic marketing and online trading of network enterprises. A new customer classification algorithm for electronic commerce enterprises is advanced based on analyzing customer characteristics and behaviors. First, based on consumer characteristics and be...

This paper aimed to build unified pattern per customer not only represent normal behavior but also Fraud pattern that’s represented previously and confirmed as fraud transactions that’s facilitate studding fraudsters behavior. An enhancement for the proposed algorithm of Fraud Miner has been proposed. This enhancement involves introducing LINGO clustering Data mining algorithm by replacing Apri...

PurposeHotel Industry is one of the most substantial factors for Tourism Industry. It could provide the necessary substructures for Tourism. Therefore the growth in Tourism industry depends on growth in Hotel industry. Hotel industry had a major growth in recent years in Iran; therefore the purpose of this paper is to explore the customer satisfaction in hotel industry. This paper aims to ident...

for winning in global competition, companies need to recognition and monitoring of customer's behavior to forecast their behavior and desires earlier than competitors. this research tries to recognize the attributes which lead to customer churn. for this, behavior of 3150 subscribers of an iranian mobile operator, has observed during one year and trends of them has analyzed by a customized...

An efficient customer behavior analysis is important for good Recommender System. Customer transaction clustering is usually the first step towards the analysis of customer behavior. Traditionally data mining techniques are deployed in order to provide effective recommendation based on large population of customer transactions in real time. Customer transactions are likely to be imprecise and i...