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Using social ties in group recommendation
Author(s)
Date Issued
2011-08-31
Date Available
2012-01-26T14:47:56Z
Abstract
The social web is a mass of activity, petabytes of data are generated yearly. The social web has proven to be a great resource for new recommender system techniques and ideas. However it would appear that typically these techniques are not so social, as they only generate recommendations for a user acting alone. In this paper we take the social graph data and preference content (via Facebook) of 94 user study participants and generate social group recommendations for them and their friends. We evaluate how different aggregation policies perform in deciding the final group recommendation. Our findings show that in an offline evaluation an aggregation policy which takes into consideration social weighting outperforms other aggregation policies.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
Intelligent Systems Research Centre
Subject – LCSH
Recommender systems (Information filtering)
Web co-browsing
Online social networks
Language
English
Status of Item
Peer reviewed
Part of
AICS 2011 : Proceedings of the 22nd Irish Conference on Artificial Intelligence and Cognitive Science : 31 August - 2 September, 2011 : University of Ulster - Magee
Conference Details
Paper presented at the 22nd Irish Conference on Artificial Intelligence and Cognitive Science (AICS 2011), University of Ulster, Northern Ireland, 31 August - 2 September, 2011
This item is made available under a Creative Commons License
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