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  5. Mining Product Experiences from User Generated Reviews: A Recommender Systems Perspective
 
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Mining Product Experiences from User Generated Reviews: A Recommender Systems Perspective

Author(s)
Muhammad, Khalil 
Lawlor, Aonghus 
Rafter, Rachael 
Smyth, Barry 
Uri
http://hdl.handle.net/10197/6456
Date Issued
September 2014
Date Available
01T12:28:33Z April 2015
Abstract
We have employed algorithms described in to mine opinions from TripAdvisor hotel reviews; we have experimented with different parameters to learn which provided more meaningful extractions. Secondly, we have considered opinion summarization and search similar to. We have implemented a retrieval strategy that accepts natural language queries based on opinions from reviews. Additionally, we have proposed various methods of summarizing opinions based on statistical metrics. Currently, we are experimenting with feature quality metrics. Our aim is to establish a relevance score that describes the usefulness of extracted opinions. We are also running recommendation experiments using different versions the extracted opinions.
Other Sponsorship
Science Foundation Ireland
Type of Material
Conference Publication
Keywords
  • Recommender systems

  • Product descriptions

Web versions
http://www.iccbr.org/iccbr14/
Language
English
Status of Item
Peer reviewed
Conference Details
22nd International Conference on Case-Based Reasoning, Cork, Ireland, 29 September - 01 October 2014
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
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insight_publication.pdf

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128.3 KB

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Insight Research Collection
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