An Intelligent TV-Shopping Application that Provides Recommendations

In this paper we describe an intelligent and adaptive TV-shopping application that has been designed to recommend mobile phones to perspective buyers. The application is called iTVMobi and its adaptivity is achieved through a user model. The user model monitors users´ behaviour and adapts the interaction to them depending on their inferred interests. The underlying reasoning is based on grouping users with similar tastes by the use of k-means clustering. After the clustering, representative vectors of users´ preferences are calculated and compared through association rules with the products database in order to achieve product recommendations.