Identification of Mazandaran Telecommunication Company Fixed phone subscribers using H-Means and W-K-Means Algorithm

In recent years, companies' interaction with customers has changed significantly. Organizations require a proper understanding of customers and their needs in order to succeed in business. Customer Relationship Management (CRM) using data mining techniques, to discover hidden and valuable knowledge in data and information of organizations, provide the conditions for optimal management of customer relationships, as organizations never lose opportunity for more selling and better customer satisfaction as earning customer loyalty, as well as improve their profitability. One method of customer identification is customer clustering approach. This operation is used when we want to find groups of similar data without having a prediction on pre-existing similarities. This paper proposes a model based on H-Means and W-K-Means algorithm that customers are compared with the optimal number of clusters and clustering results are evaluated in terms of quality

Identification of Mazandaran Telecommunication Company Fixed phone subscribers using H-Means and W-K-Means Algorithm Keywords:

Data mining , clustering , K-Means algorithms