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Sticking with a Winning Team: Better Neighbour Selection for Conversational Collaborative Recommendation
Date Issued
2007-08
Date Available
2013-10-01T10:15:02Z
Abstract
Conversational recommender systems have recently emerged
as useful alternative strategies to their single-shot counterpart, especially
given their ability to expose a user’s current preferences. These systems
use conversational feedback to hone in on the most suitable item for
recommendation by improving the mechanism that finds useful collaborators.
We propose a novel architecture for performing recommendation
that incorporates information about the individual performance of
neighbours during a recommendation session, into the neighbour retrieval
mechanism. We present our architecture and a set of preliminary evaluation
results that suggest there is some merit to our approach.We examine
these results and discuss what they mean for future research.
Type of Material
Conference Publication
Keywords
Language
English
Status of Item
Not peer reviewed
Part of
Proceedings of the 18th Irish Conference on Artificial Intelligence and Cognitive Science (AICS 07), Dublin, Ireland, August, 2007
Conference Details
The 18th Irish Conference on Artificial Intelligence and Cognitive Science (AICS 07), Dublin, Ireland, 29-31 August, 2007
This item is made available under a Creative Commons License
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