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Paper Abstract and Keywords
Presentation 2020-01-23 14:40
e-Travel: Automatical Travel Support Site Generation based on Review Analysis per Travel Style
Naoki Kawamura, Komei Arasawa, Shun Hattori (Muroran Inst. of Tech.) IN2019-67
Abstract (in Japanese) (See Japanese page) 
(in English) For traveling and sightseeing, many people often use travel review sites and travel information magazines. Some travel review sites allow users to browse sightseeing spots and food of a target place depending on travel styles such as "alone," "friend," "family," and "couple." Some users try to utilize such a function while planning their travel and/or stopping over at somewhere (not a planed place) in their travel. However, the function of search per travel style of the existing travel review sites is not enough useful when a traveler searches for sightseeing spots and restaurants by querying a target place and adding "friend" as a travel style condition, because the search results for some places are not helpful for her/him due to lack of reviews. Therefore, this paper aims at developing an automatical travel support site generation system that extracts place-specific spots and offers users with the ranking of them per travel style, by exhaustively collecting place-specific reviews from many travel review sites and analyzing them classified per travel style.
Keyword (in Japanese) (See Japanese page) 
(in English) Travel Support / Text Classification / Information Extraction / Web Mining / Machine Learning / / /  
Reference Info. IEICE Tech. Rep., vol. 119, no. 384, IN2019-67, pp. 13-18, Jan. 2020.
Paper # IN2019-67 
Date of Issue 2020-01-16 (IN) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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)
Download PDF IN2019-67

Conference Information
Committee IN  
Conference Date 2020-01-23 - 2020-01-24 
Place (in Japanese) (See Japanese page) 
Place (in English) WINC AICHI 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Contents Distribution, Social Networking Services, Data Analytics and Processing Platform, Big data, etc. 
Paper Information
Registration To IN 
Conference Code 2020-01-IN 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) e-Travel: Automatical Travel Support Site Generation based on Review Analysis per Travel Style 
Sub Title (in English)  
Keyword(1) Travel Support  
Keyword(2) Text Classification  
Keyword(3) Information Extraction  
Keyword(4) Web Mining  
Keyword(5) Machine Learning  
1st Author's Name Naoki Kawamura  
1st Author's Affiliation Muroran Institute of Technology (Muroran Inst. of Tech.)
2nd Author's Name Komei Arasawa  
2nd Author's Affiliation Muroran Institute of Technology (Muroran Inst. of Tech.)
3rd Author's Name Shun Hattori  
3rd Author's Affiliation Muroran Institute of Technology (Muroran Inst. of Tech.)
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Speaker Author-1 
Date Time 2020-01-23 14:40:00 
Presentation Time 25 minutes 
Registration for IN 
Paper # IN2019-67 
Volume (vol) vol.119 
Number (no) no.384 
Page pp.13-18 
Date of Issue 2020-01-16 (IN) 

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