A Case-Based Solution to the Cold-Start Problem in Group Recommenders
Abstract
In this paper we offer a potential solution to the cold-start problem in group recommender systems. To do so, we use information about previous group recommendation events and copy ratings from a user who played a similar role in some previous group event. We show that copying in this way, i.e. conditioned on groups, is superior to copying nothing and also superior to copying ratings from the most similar user known to the system.
Cite
Text
Sánchez et al. "A Case-Based Solution to the Cold-Start Problem in Group Recommenders." International Joint Conference on Artificial Intelligence, 2013.Markdown
[Sánchez et al. "A Case-Based Solution to the Cold-Start Problem in Group Recommenders." International Joint Conference on Artificial Intelligence, 2013.](https://mlanthology.org/ijcai/2013/sanchez2013ijcai-case/)BibTeX
@inproceedings{sanchez2013ijcai-case,
title = {{A Case-Based Solution to the Cold-Start Problem in Group Recommenders}},
author = {Sánchez, Lara Quijano and Bridge, Derek G. and Díaz-Agudo, Belén and Recio-García, Juan Antonio},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2013},
pages = {3042-3046},
url = {https://mlanthology.org/ijcai/2013/sanchez2013ijcai-case/}
}