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Paper Abstract and Keywords
Presentation 2016-06-05 10:20
A Comparative Analysis of Sizzle words for Automatic Extraction of "Palatability"
Maki Morita (Wakayama Univ.), Eiji Aramaki (NAIST), Akiyo Nadamoto (Konan Univ.), Mai Miyabe (Wakayama Univ.) TL2016-11 NLC2016-11
Abstract (in Japanese) (See Japanese page) 
(in English) Nowadays, the restaurant search services on the Internet become popular, people use them when they search the new restaurant.
It is, however, difficult for users to find their desired restaurant by using existing restaurant search services.
In this study, we propose new restaurant search system which searches for user's desired restaurant based on sizzle word such as ``MOCHI-MOCHI" and ``SAKU-SAKU". on the Twitter.
In this paper, as a first step of the study, we examine the possibility of automatic classification of sizzle tweet for three types as ``taste-type", ``texture-type", and ``information-type" based on our sizzle words classifier system.
From our examine, we defined (1)we can automatic classify tweets with sizzle words according to three types, (2)there are sizzle word pair which classify each other in a three types, and (3)we can classify ``taste-type" and ``texture-type" each other.
Keyword (in Japanese) (See Japanese page) 
(in English) Sizzle related words / Microblog / Twitter / Automatic classification / Restaurant recommendation / / /  
Reference Info. IEICE Tech. Rep., vol. 116, no. 78, NLC2016-11, pp. 53-58, June 2016.
Paper # NLC2016-11 
Date of Issue 2016-05-28 (TL, NLC) 
ISSN Print edition: ISSN 0913-5685    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)
Download PDF TL2016-11 NLC2016-11

Conference Information
Committee NLC TL  
Conference Date 2016-06-04 - 2016-06-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Otaru University of Commerce 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Application of natural language proessing and linguistic analysis, and general topic of NLP 
Paper Information
Registration To NLC 
Conference Code 2016-06-NLC-TL 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Comparative Analysis of Sizzle words for Automatic Extraction of "Palatability" 
Sub Title (in English)  
Keyword(1) Sizzle related words  
Keyword(2) Microblog  
Keyword(3) Twitter  
Keyword(4) Automatic classification  
Keyword(5) Restaurant recommendation  
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1st Author's Name Maki Morita  
1st Author's Affiliation Wakayama University (Wakayama Univ.)
2nd Author's Name Eiji Aramaki  
2nd Author's Affiliation Nara Institute of Science and Technology (NAIST)
3rd Author's Name Akiyo Nadamoto  
3rd Author's Affiliation Konan University (Konan Univ.)
4th Author's Name Mai Miyabe  
4th Author's Affiliation Wakayama University (Wakayama Univ.)
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Speaker Author-1 
Date Time 2016-06-05 10:20:00 
Presentation Time 25 minutes 
Registration for NLC 
Paper # TL2016-11, NLC2016-11 
Volume (vol) vol.116 
Number (no) no.77(TL), no.78(NLC) 
Page pp.53-58 
#Pages 6 
Date of Issue 2016-05-28 (TL, NLC) 

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