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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

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Author(s)
Dong, Ruihai 
Smyth, Barry 
Uri
http://hdl.handle.net/10197/9026
Date Issued
17 July 2016
Date Available
03T16:04:29Z November 2017
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
Keywords
  • Recommender Systems

DOI
10.1145/2930238.2930276
Language
English
Status of Item
Peer reviewed
Part of
UMAP '16 Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization
Description
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/
Owning collection
Insight Research Collection
Scopus© citations
7
Acquisition Date
Jan 28, 2023
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889
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