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CATS: A Synchronous Approach to Collaborative Group Recommendation

Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, Melbourne Beach, Florida, USA, May 11-13, 2006, : 86-91, 2006.
Authors: Kevin McCarthy and Maria Salam{\'o} and Lorcan Coyle and Lorraine McGinty and Barry Smyth and Paddy Nixon
Editors: Geoff Sutcliffe and Randy Goebel
Description: Lorcan Coyle's Bibliography
Tags: collaborative recommender_systems
Abstract: Group recommender systems introduce a whole set of new challenges for recommender systems research. The notion of generating a set of recommendations that will satisfy a group of users with potentially competing interests is challenging in itself. In addition to this we must consider how to record and combine the preferences of many different users as they engage in simultaneous recommendation dialogs. In this paper we introduce a group recommender system that is designed to provide assistance to a group of friends trying the plan a skiing vacation. The system uses the DiamondTouch interactive tabletop to allow up to 4 users to simultaneously engage in parallel recommendation sessions and we describe how personal and shared profiles and interaction spaces can be managed to generate sets of recommendations for the individual as well as the group.
| BibTeX  
@inproceedings{Mccarthy2006Cats,
title = {CATS: A Synchronous Approach to Collaborative Group Recommendation},
author = {Kevin McCarthy and Maria Salam{\'o} and Lorcan Coyle and Lorraine McGinty and Barry Smyth and Paddy Nixon},
booktitle = {Proceedings of the Nineteenth International Florida Artificial Intelligence Research Society Conference, Melbourne Beach, Florida, USA, May 11-13, 2006},
editor = {Geoff Sutcliffe and Randy Goebel},
month = {May},
pages = {86-91},
publisher = {AAAI Press},
year = {2006},
description = {Lorcan Coyle's Bibliography},
abstract = {Group recommender systems introduce a whole set of new challenges for recommender systems research. The notion of generating a set of recommendations that will satisfy a group of users with potentially competing interests is challenging in itself. In addition to this we must consider how to record and combine the preferences of many different users as they engage in simultaneous recommendation dialogs. In this paper we introduce a group recommender system that is designed to provide assistance to a group of friends trying the plan a skiing vacation. The system uses the DiamondTouch interactive tabletop to allow up to 4 users to simultaneously engage in parallel recommendation sessions and we describe how personal and shared profiles and interaction spaces can be managed to generate sets of recommendations for the individual as well as the group.},
keywords = {collaborative recommender_systems }
}