A user preference perception model using data mining on a Web-based Environment

In a competitive environment, how to provide the information and products to meet the requirements of customers and improve the customer satisfaction will be the key criteria to measure a company’s competitiveness. Customer Relationship Management (CRM) becomes an important issue in any business market gradually. Using information technology, businesses can achieve their requirements for one to one marketing more efficiently with lower cost, labor and time. In this paper, we proposed a user preference perception model by using data mining technology on a web-based environment. First, the users’ web browse records are aggregated. Second, fuzzy set theory and most sequential pattern mining algorithm are used to infer the users’ preference changes in a period. After the test had processed, we use the on-line questionnaire to investigate the customer satisfaction degree from all participators. The results show that the degree of satisfaction was up to 72% for receiving the new information of participants whose preferences had been changed. It indicates that the proposed system can effectively perceive the change of preference for users on a web environment