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Explanation-based Ranking in Opinionated Recommender Systems

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Author(s)
Muhammad, Khalil 
Lawlor, Aonghus 
Smyth, Barry 
Uri
http://hdl.handle.net/10197/9946
Date Issued
21 September 2018
Date Available
15T10:05:08Z April 2019
Abstract
Explanations can help people to make better choices, but their use in recommender systems has so far been limited to the annotation of recommendations after they have been ranked and suggested to the user. In this paper we argue that explanations can also be used to rank recommendations. We describe a technique that uses the strength of an item’s explanation as a ranking signal – preferring items with compelling explanations – and demonstrate its efficacy on a real-world dataset.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
CEUR Workshop Proceedings
Keywords
  • Recommender systems

  • Ranking signal

  • Informed decision mak...

Web versions
http://aics2016.ucd.ie/
Language
English
Status of Item
Peer reviewed
Description
The 24th Irish Conference on Artificial Intelligence and Cognitive Science, University College Dublin, Ireland, 20-21 September 2016
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Insight Research Collection
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Acquisition Date
Feb 2, 2023
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