Context-Tree Recommendation vs Matrix-Factorization: Algorithm Selection and Live Users Evaluation

Stéphane Martin, Boi Faltings, Vincent Schickel. Context-Tree Recommendation vs Matrix-Factorization: Algorithm Selection and Live Users Evaluation. In The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019. pages 9534-9540, AAAI Press, 2019. [doi]

@inproceedings{MartinFS19,
  title = {Context-Tree Recommendation vs Matrix-Factorization: Algorithm Selection and Live Users Evaluation},
  author = {Stéphane Martin and Boi Faltings and Vincent Schickel},
  year = {2019},
  url = {https://aaai.org/ojs/index.php/AAAI/article/view/5012},
  researchr = {https://researchr.org/publication/MartinFS19},
  cites = {0},
  citedby = {0},
  pages = {9534-9540},
  booktitle = {The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019},
  publisher = {AAAI Press},
  isbn = {978-1-57735-809-1},
}