Knowledge-based Recommendation: Technologies and Experiences from Projects
Alexander Felfernig, See Profile, Bartosz Gula, Alexander Felfernig, Erich Teppan · 2006
Recommender applications support decision-making processes by helping online cus-tomers to identify products more effectively. Recommendation problems have a long history as a successful application area of Artificial Intelligence (AI) and the interest in recommender applications has dramatically increased due to the demand for personaliza-tion technologies by large and successful e-Commerce environments. Knowledge-based recommender applications are especially useful for improving the accessibility of com-plex products such as financial services or computers. Such products demand a more profound knowledge from customers than simple products such as CDs or movies. In this paper we focus on a discussion of AI technologies needed for the development of knowledge-based recommender applications. In this context, we report experiences from commercial projects and present the results of a study which investigated key factors influencing the acceptance of knowledge-based recommender technologies by end-users.