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  5. From More-Like-This to Better-Than-This: Hotel Recommendations from User Generated Reviews
 
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From More-Like-This to Better-Than-This: Hotel Recommendations from User Generated Reviews

Author(s)
Dong, Ruihai  
Smyth, Barry  
Uri
http://hdl.handle.net/10197/9026
Date Issued
2016-07-17
Date Available
2017-11-03T16:04:29Z
Abstract
To help users discover relevant products and items recommender systems must learn about the likes and dislikes of users and the pros and cons of items. In this paper, we present a novel approach to building rich feature-based user profiles and item descriptions by mining user-generated reviews. We show how this information can be integrated into recommender systems to deliver better recommendations and an improved user experience.
Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Publisher
ACM
Copyright (Published Version)
2016 the authors
Subjects

Recommender Systems

DOI
10.1145/2930238.2930276
Language
English
Status of Item
Peer reviewed
Journal
UMAP '16 Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization
Conference Details
UMAP ’16, Halifax, NS, Canada
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

176.85 KB

Format

Adobe PDF

Checksum (MD5)

61be60f9e6f49ddacc350047a36974a6

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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