Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Intelligent food planning: personalized recipe recommendation
Proceedings of the 15th international conference on Intelligent user interfaces
A survey of collaborative filtering techniques
Advances in Artificial Intelligence
Deriving a recipe similarity measure for recommending healthful meals
Proceedings of the 16th international conference on Intelligent user interfaces
Recipe recommendation using ingredient networks
Proceedings of the 3rd Annual ACM Web Science Conference
Intelligent menu planning: recommending set of recipes by ingredients
Proceedings of the ACM multimedia 2012 workshop on Multimedia for cooking and eating activities
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The Netflix prize has rejuvenated a widespread interest in the matrix factorization approach for collaborative filtering. We describe a simple algorithm for incorporating content information directly into this approach. We present experimental evidence using recipe data to show that this not only improves recommendation accuracy but also provides useful insights about the contents themselves that are otherwise unavailable.