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 Ko{\vs}ir},
  journal={Interact. Comput.},
  year={2013},
  volume={25},
  pages={74-90}
}
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… 
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110 Citations
Highly Influential Citations
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Background Citations
40
Methods Citations
32
Results Citations
1

110 Citations

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Progress in context-aware recommender systems - An overview

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38 References

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  • Zhang YujieWang Licai
  • Computer Science
    2010 5th International Conference on Computer Science & Education
  • 2010
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