Rating Personalization Improves Accuracy: A Proportion-Based Baseline Estimate Model for Collaborative Recommendation

Zhenhua Tan, Liangliang He, Hong Li, Xingwei Wang. Rating Personalization Improves Accuracy: A Proportion-Based Baseline Estimate Model for Collaborative Recommendation. In Shangguang Wang, Ao Zhou, editors, Collaborate Computing: Networking, Applications and Worksharing - 12th International Conference, CollaborateCom 2016, Beijing, China, November 10-11, 2016, Proceedings. Volume 201 of Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, pages 104-114, Springer, 2016. [doi]

@inproceedings{TanHLW16,
  title = {Rating Personalization Improves Accuracy: A Proportion-Based Baseline Estimate Model for Collaborative Recommendation},
  author = {Zhenhua Tan and Liangliang He and Hong Li and Xingwei Wang},
  year = {2016},
  doi = {10.1007/978-3-319-59288-6_10},
  url = {https://doi.org/10.1007/978-3-319-59288-6_10},
  researchr = {https://researchr.org/publication/TanHLW16},
  cites = {0},
  citedby = {0},
  pages = {104-114},
  booktitle = {Collaborate Computing: Networking, Applications and Worksharing - 12th International Conference, CollaborateCom 2016, Beijing, China, November 10-11, 2016, Proceedings},
  editor = {Shangguang Wang and Ao Zhou},
  volume = {201},
  series = {Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering},
  publisher = {Springer},
  isbn = {978-3-319-59288-6},
}