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  5. A Multi-Domain Analysis of Explanation-Based Recommendation using User-Generated Reviews
 
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A Multi-Domain Analysis of Explanation-Based Recommendation using User-Generated Reviews

Author(s)
Muhammad, Khalil  
Lawlor, Aonghus  
Smyth, Barry  
Uri
http://hdl.handle.net/10197/10126
Date Issued
2018-05-23
Date Available
2019-04-24T12:05:34Z
Abstract
This paper extends recent work on the use of explanations in recommender systems. In particular, we show how explanations can be used to rank as well as justify recommendations, then we compare the results to more conventional recommendation approaches, in three large-scale application domains.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
AAAI Publications
Copyright (Published Version)
2018 Association for the Advancement of Artificial Intelligence
Subjects

Explanations

Recommender systems

Artificial intelligen...

Explanation-based rec...

Web versions
https://sites.google.com/site/flairs31conference/
https://www.aaai.org/ocs/index.php/AAAI/FLAIRS18/index
Language
English
Status of Item
Peer reviewed
Conference Details
The Thirty-First International FLAIRS Conference (FLAIRS-31), Florida, United States of America, 21-23 May 2018
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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insight_publication.pdf

Size

1.18 MB

Format

Adobe PDF

Checksum (MD5)

61f68e926562d3a6899fceadb58f0e96

Owning collection
Insight Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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