188/4 E-Commerce Group
Institute of Software Technology and Interactive Systems
Vienna University of Technology
Favoritenstrasse 9-11/188, A-1040 Vienna, Austria

Observing Group Decision Making Processes

Type: 
Speech with proceedings
Abstract: 
Most research on group recommender systems relies on the assumption that individuals have conflicting preferences; in order to generate group recommendations the system should identify a fair way of aggregating these preferences. Both empirical studies and theoretical frameworks have tried to identify the most effective preference aggregation techniques without coming to definite conclusions. In this paper, we propose to approach group recommendation from the group dynamics perspective and analyze the group decision making process for a particular task (in the travel domain). We observe several individual and group properties and correlate them to choice satisfaction. Supported by these initial results we therefore advocate for the development of new group recommendation techniques that consider group dynamics and support the full group decision making process.
Hidden Keywords: 
Department Focus: 
Business Informatics
TU Focus: 
Information and Communication Technology
Proceedings: 
Proceedings of the 10th ACM Conference on Recommender systems
Publisher: 
ACM
Year: 
2016
ISBN: 
ISBN: 978-1-4503-4035-9
Pages: 
147 - 150
Accepted: 
Acceptance undecided
Invited: 
Reference: 
<u>A. Delic</u>, J. Neidhardt, T. Nguyen, F. Ricci, L. Rook, H. Werthner, M. Zanker: <br>"<i><a href="http://dl.acm.org/citation.cfm?id=2959168" target="_blank" class="publist">Observing Group Decision Making Processes</a></i>"; <br>Talk: 10th ACM Conference on Recommender Systems, Boston, MA, USA; 09-15-2016 - 09-19-2016; in: "<i>Proceedings of the 10th ACM Conference on Recommender systems</i>", ACM, (2016), ISBN: 978-1-4503-4035-9; 147 - 150.<br><br> <a href="https://publik.tuwien.ac.at/showentry.php?ID=250530&lang=2" class="publist"><i>More information</i></a><br><br>
Abstract German: 
Most research on group recommender systems relies on the assumption that individuals have conflicting preferences; in order to generate group recommendations the system should identify a fair way of aggregating these preferences. Both empirical studies and theoretical frameworks have tried to identify the most effective preference aggregation techniques without coming to definite conclusions. In this paper, we propose to approach group recommendation from the group dynamics perspective and analyze the group decision making process for a particular task (in the travel domain). We observe several individual and group properties and correlate them to choice satisfaction. Supported by these initial results we therefore advocate for the development of new group recommendation techniques that consider group dynamics and support the full group decision making process.