Acquiring Customer Preferences for Information Filtering: a Heuristic-Statistical Approach

The increasing availability of a large number of services in the interactive multi-media information infrastructure means that customers have a diverse and large collection of choices open to them. One method of assisting customers to navigate through this large collection is to use information filtering to extract only the information relevant to an end-user according to his/her long-term preferences. In this paper, we describe a mechanism to acquire a customer’s long-term preferences (customer profile), and then utilise the acquired profile to suggest selections that may be of interest to the customer. The profile is acquired on the basis of a customer’s habits using a Heuristic-Statistical approach, and is used to create information filters. Our mechanism has been incorporated into an experimental Video On Demand (VOD) service.