Sciweavers

Share
IADIS
2003

Prediction Strategies in a TV Recommender System - Method and Experiments

8 years 9 months ago
Prediction Strategies in a TV Recommender System - Method and Experiments
Predicting the interests of a user in information is an important process in personalized information systems. In this paper, we present a way to create prediction engines that allow prediction techniques to be easily combined into prediction strategies. Prediction strategies choose one or a combination of prediction techniques at the moment a prediction is required, taking into account the most up -to-date knowledge about the current user, other users, the information and the system itself. Results of two experiments show that prediction strategies improve both the accuracy and stability of prediction engines. One of these experiments involves a TV recommender system. This paper describes the method of prediction strategies, how they have been applied in the TV recommender system and results of the experiment in detail. KEYWORDS Personalization, Adaptive Systems, Recommender Systems, User Modeling
Mark van Setten, Mettina Veenstra, Anton Nijholt,
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where IADIS
Authors Mark van Setten, Mettina Veenstra, Anton Nijholt, Betsy van Dijk
Comments (0)
books