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Using a critic to promote less popular candidates in a people-to-people recommender system
Citation
Krzywicki, A and Wobcke, W and Cai, X and Bain, M and Mahidadia, A and Compton, P and Kim, YS, Using a critic to promote less popular candidates in a people-to-people recommender system, Proceedings of the 24th Innovative Applications of Artificial Intelligence Conference 2012, 22-26 July 2012, Toronto, Canada, pp. 2305-2310. ISBN 978-1-57735-568-7 (2012) [Refereed Conference Paper]
Copyright Statement
Copyright 2012 AAAI
Official URL: http://www.aaai.org/Press/Proceedings/aaai12.php
Abstract
This paper shows how to improve the recommendations of
an interaction-based collaborative filtering (IBCF) recommender
used in online dating. Previous work has shown that
IBCF works well in this domain, although it tends to rank
popular candidates highly, which leads to these users receiving
a large number of contacts. We address this problem by
using a Decision Tree model as a "critic" to re-rank the candidates
generated by IBCF, effectively promoting less popular
candidates. This method was first evaluated on historical data
from a large online dating site and then trialled live on the
same site by providing recommendations to a large number of
users throughout a 9 week period. The live trial confirmed the
consistency of the analysis on historical data and the ability of
the method to generate suitable candidates over an extended
period. Our recommendations gave higher success rates than
those for a control group made with a baseline recommender.
Item Details
Item Type: | Refereed Conference Paper |
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Keywords: | recommender systems, social network analysis |
Research Division: | Information and Computing Sciences |
Research Group: | Artificial intelligence |
Research Field: | Artificial intelligence not elsewhere classified |
Objective Division: | Information and Communication Services |
Objective Group: | Information systems, technologies and services |
Objective Field: | Application software packages |
UTAS Author: | Kim, YS (Dr Yang Kim) |
ID Code: | 94669 |
Year Published: | 2012 |
Deposited By: | Information and Communication Technology |
Deposited On: | 2014-09-15 |
Last Modified: | 2014-12-09 |
Downloads: | 0 |
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