Abstract
Previous personalized DTV recommendation systems focus only on viewers' historical viewing records or demographic data. This study proposes a new recommending mechanism from a user oriented perspective. The recommending mechanism is based on user properties such as Activities, Interests, Moods, Experiences, and Demographic information - AIMED. The AIMED data is fed into a neural network model to predict TV viewers' program preferences. Evaluation results indicate that the AIMED model significantly increases recommendation accuracy and decreases prediction errors compared to the conventional model. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Hsu, S. H., Wen, M. H., Lin, H. C., Lee, C. C., & Lee, C. H. (2007). AIMED- A personalized TV recommendation system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4471 LNCS, pp. 166–174). Springer Verlag. https://doi.org/10.1007/978-3-540-72559-6_18
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