IEICE TRANSACTIONS on Information
Purpose-Feature Relationship Mining from Online Reviews towards Purpose-Oriented Recommendation
Summary :
To help with decision making, online shoppers tend to go through both a list of a product's features and functionality provided by the vendor, as well as a list of reviews written by other users. Unfortunately, this process is ineffective when the buyer is confronted with large amounts of information, particularly when the buyer has limited experience with and knowledge of the product. In order to avoid this problem, we propose a framework of purpose-oriented recommendation that presents a ranked list of products suitable for a designated user purpose by identifying important product features to fulfill the purpose from online reviews. As technical foundation for realizing the framework, we propose several methods to mine relation between user purposes and product features from the consumer reviews. Using digital camera reviews on Amazon.com, the experimental results show that our proposed method is both effective and stable, with an acceptable rate of precision and recall.
- Publication
- IEICE TRANSACTIONS on Information Vol.E101-D No.4 pp.1021-1029
- Publication Date
- 2018/04/01
- Publicized
- 2018/01/18
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2017DAP0013
- Type of Manuscript
- Special Section PAPER (Special Section on Data Engineering and Information Management)
- Category
Authors
Sopheaktra YONG
Kyoto University
Yasuhito ASANO
Kyoto University
Keyword
Latest Issue
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Sopheaktra YONG, Yasuhito ASANO, "Purpose-Feature Relationship Mining from Online Reviews towards Purpose-Oriented Recommendation" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 4, pp. 1021-1029, April 2018, doi: 10.1587/transinf.2017DAP0013.
Abstract: To help with decision making, online shoppers tend to go through both a list of a product's features and functionality provided by the vendor, as well as a list of reviews written by other users. Unfortunately, this process is ineffective when the buyer is confronted with large amounts of information, particularly when the buyer has limited experience with and knowledge of the product. In order to avoid this problem, we propose a framework of purpose-oriented recommendation that presents a ranked list of products suitable for a designated user purpose by identifying important product features to fulfill the purpose from online reviews. As technical foundation for realizing the framework, we propose several methods to mine relation between user purposes and product features from the consumer reviews. Using digital camera reviews on Amazon.com, the experimental results show that our proposed method is both effective and stable, with an acceptable rate of precision and recall.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2017DAP0013/_p
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@ARTICLE{e101-d_4_1021,
author={Sopheaktra YONG, Yasuhito ASANO, },
journal={IEICE TRANSACTIONS on Information},
title={Purpose-Feature Relationship Mining from Online Reviews towards Purpose-Oriented Recommendation},
year={2018},
volume={E101-D},
number={4},
pages={1021-1029},
abstract={To help with decision making, online shoppers tend to go through both a list of a product's features and functionality provided by the vendor, as well as a list of reviews written by other users. Unfortunately, this process is ineffective when the buyer is confronted with large amounts of information, particularly when the buyer has limited experience with and knowledge of the product. In order to avoid this problem, we propose a framework of purpose-oriented recommendation that presents a ranked list of products suitable for a designated user purpose by identifying important product features to fulfill the purpose from online reviews. As technical foundation for realizing the framework, we propose several methods to mine relation between user purposes and product features from the consumer reviews. Using digital camera reviews on Amazon.com, the experimental results show that our proposed method is both effective and stable, with an acceptable rate of precision and recall.},
keywords={},
doi={10.1587/transinf.2017DAP0013},
ISSN={1745-1361},
month={April},}
Copy
TY - JOUR
TI - Purpose-Feature Relationship Mining from Online Reviews towards Purpose-Oriented Recommendation
T2 - IEICE TRANSACTIONS on Information
SP - 1021
EP - 1029
AU - Sopheaktra YONG
AU - Yasuhito ASANO
PY - 2018
DO - 10.1587/transinf.2017DAP0013
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2018
AB - To help with decision making, online shoppers tend to go through both a list of a product's features and functionality provided by the vendor, as well as a list of reviews written by other users. Unfortunately, this process is ineffective when the buyer is confronted with large amounts of information, particularly when the buyer has limited experience with and knowledge of the product. In order to avoid this problem, we propose a framework of purpose-oriented recommendation that presents a ranked list of products suitable for a designated user purpose by identifying important product features to fulfill the purpose from online reviews. As technical foundation for realizing the framework, we propose several methods to mine relation between user purposes and product features from the consumer reviews. Using digital camera reviews on Amazon.com, the experimental results show that our proposed method is both effective and stable, with an acceptable rate of precision and recall.
ER -
English
