Paper Abstract and Keywords |
Presentation |
2019-09-27 17:25
Caputuring the correlation between consumers' preferences among different domains from E-commerce review data Gaia Suzuki, Masanao Ochi, Ichiro Sakata (The Univ. of Tokyo) NLC2019-15 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Segmentation is essential for strategical marketing, but it is considered difficult to both divide market needs among different retail domains and reveal the segmentation variables systematically. Recently, deep recommender systems became a practical solution to predict user preference using review texts as input, and has the potential to both divide and comprehend market needs. As an exploratory analysis to achieve this goal, we developed a cross-domain recommender system using Amazon review dataset to grasp the correlation of user preferences between different retail sectors. We then tried to extract essential features from the review text using latent dirichlet allocation. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
E-commerce site / segmentation / feature learning / cross-domain recommendation / LDA / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 212, NLC2019-15, pp. 35-40, Sept. 2019. |
Paper # |
NLC2019-15 |
Date of Issue |
2019-09-20 (NLC) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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NLC2019-15 |
Conference Information |
Committee |
NLC IPSJ-DC |
Conference Date |
2019-09-27 - 2019-09-28 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Future Corporation |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
The Thirteenth Text Analytics Symposium |
Paper Information |
Registration To |
NLC |
Conference Code |
2019-09-NLC-DC |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Caputuring the correlation between consumers' preferences among different domains from E-commerce review data |
Sub Title (in English) |
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Keyword(1) |
E-commerce site |
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segmentation |
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feature learning |
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cross-domain recommendation |
Keyword(5) |
LDA |
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1st Author's Name |
Gaia Suzuki |
1st Author's Affiliation |
The University of Tokyo (The Univ. of Tokyo) |
2nd Author's Name |
Masanao Ochi |
2nd Author's Affiliation |
The University of Tokyo (The Univ. of Tokyo) |
3rd Author's Name |
Ichiro Sakata |
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The University of Tokyo (The Univ. of Tokyo) |
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Speaker |
Author-1 |
Date Time |
2019-09-27 17:25:00 |
Presentation Time |
25 minutes |
Registration for |
NLC |
Paper # |
NLC2019-15 |
Volume (vol) |
vol.119 |
Number (no) |
no.212 |
Page |
pp.35-40 |
#Pages |
6 |
Date of Issue |
2019-09-20 (NLC) |
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