Predicting and Detecting the Relevant Contextual Information in a Movie-Recommender System

@article{Odic2013PredictingAD,
  title={Predicting and Detecting the Relevant Contextual Information in a Movie-Recommender System},
  author={Ante Odic and Marko Tkalcic and Jurij F. Tasic and Andrej Kosir},
  journal={Interact. Comput.},
  year={2013},
  volume={25},
  pages={74-90}
}
  • Ante Odic, Marko Tkalcic, +1 author Andrej Kosir
  • Published 2013
  • Computer Science
  • Interact. Comput.
  • Context-aware recommender system (CARS) is a highly researched and implemented way of providing a personalized service that helps users to find their desired content. One of the remaining issues is how to decide which contextual information to acquire and how to incorporate it into CARS. While the relevant contextual information will improve the recommendations, the irrelevant contextual information could have a negative impact on the recommendation accuracy. By testing the independence between… CONTINUE READING
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