An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering Algorithms

@article{Herlocker2004AnEA,
  title={An Empirical Analysis of Design Choices in Neighborhood-Based Collaborative Filtering Algorithms},
  author={Jonathan L. Herlocker and Joseph A. Konstan and John Riedl},
  journal={Information Retrieval},
  year={2004},
  volume={5},
  pages={287-310}
}
Collaborative filtering systems predict a user's interest in new items based on the recommendations of other people with similar interests. Instead of performing content indexing or content analysis, collaborative filtering systems rely entirely on interest ratings from members of a participating community. Since predictions are based on human ratings, collaborative filtering systems have the potential to provide filtering based on complex attributes, such as quality, taste, or aesthetics. Many… Expand
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