A case-based solution to the cold-start problem in group recommenders. Quijano-Sánchez, L., Bridge, D., Díaz-Agudo, B., & Recio-García, J. In IJCAI International Joint Conference on Artificial Intelligence, 2013.
abstract   bibtex   
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.
@inproceedings{
 title = {A case-based solution to the cold-start problem in group recommenders},
 type = {inproceedings},
 year = {2013},
 identifiers = {[object Object]},
 id = {60c09b79-dfc0-3829-98d1-d6b0eea16139},
 created = {2019-12-12T11:44:31.487Z},
 file_attached = {false},
 profile_id = {b1a06709-e10b-31fa-a43e-738b5ff69456},
 last_modified = {2019-12-12T11:44:31.487Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {false},
 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.},
 bibtype = {inproceedings},
 author = {Quijano-Sánchez, L. and Bridge, D. and Díaz-Agudo, B. and Recio-García, J.A.},
 booktitle = {IJCAI International Joint Conference on Artificial Intelligence}
}

Downloads: 0