Evaluation of Group Profiling Strategies
Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence. Pages 2728-2732.
Abstract
Most of the existing personalization systems such as content recommenders or targeted ads focus on individual users and ignore the social situation in which the services are consumed. However, many human activities are social and involve several in-dividuals whose tastes and expectations must be taken into account by the system. When a group profile is not available, different profile aggrega-tion strategies can be applied to recommend ade-quate items to a group of users based on their indi-vidual profiles. We consider an approach intended to determine the factors that influence the choice of an aggregation strategy. We present evaluations made on a large-scale dataset of TV viewings, where real group interests are compared to the pre-dictions obtained by combining individual user profiles according to different strategies.
@inproceedings{ijcai2011p454,
title = {Evaluation of Group Profiling Strategies},
author = {Senot, Christophe and Kostadinov, Dimitre and Bouzid, Makram and Picault, Jérôme and Aghasaryan, Armen},
booktitle = {Proceedings of the Twenty-Second International Joint Conference on
Artificial Intelligence, {IJCAI-11}},
publisher = {AAAI Press/International Joint Conferences on Artificial Intelligence},
editor = {Toby Walsh},
pages = {2728--2732},
year = {2011},
month = {7},
doi = {10.5591/978-1-57735-516-8/IJCAI11-454},
url = {https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-454},
}
TY - CPAPER TI - Evaluation of Group Profiling Strategies AU - Senot, Christophe AU - Kostadinov, Dimitre AU - Bouzid, Makram AU - Picault, Jérôme AU - Aghasaryan, Armen T2 - Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI-11 PB - AAAI Press/International Joint Conferences on Artificial Intelligence PY - 2011 SP - 2728 EP - 2732 DO - 10.5591/978-1-57735-516-8/IJCAI11-454 UR - https://doi.org/10.5591/978-1-57735-516-8/IJCAI11-454 ER -Copied
Machine-readable versions of this paper, for tools and AI agents: