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Paper Abstract and Keywords
Presentation 2018-09-06 15:15
Tag recommendation based on the relationship with user popularity on SNS
Xueting Wang, Toshihiko Yamasaki (UTokyo) MVE2018-17
Abstract (in Japanese) (See Japanese page) 
(in English) In the content sharing service such as SNS, there are some scores which can express the degree of popularity, such as the number of views of images or videos. A high popularity score is expected by both general users and corporate promotion. In this paper, we propose a tag recommendation method to increase the popularity score.The proposed algorithm is based on PageRank, FolkRank and FolkPopularityRank (FP-Rank) algorithms.This algorithm not only uses co-occurrence between tags, but also considers the popularity degree of users and posted contents with these tags. Thus we can rank tags based on the influence on popularity.The proposed method learned with a total of 60,000 post images with tags from Flickr's public data sets and made tag recommendation with 2000 test data.In addition, we constructed a model that can predict the number of views by using tags and posted images as features. Using the prediction model, we evaluated the effect of increasing popularity of each method by adding recommended tags as features to compare the change in the number of predicted viewing numbers.
Keyword (in Japanese) (See Japanese page) 
(in English) Social network service / tag recommendation / graph model / / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 211, MVE2018-17, pp. 25-30, Sept. 2018.
Paper # MVE2018-17 
Date of Issue 2018-08-30 (MVE) 
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 MVE2018-17

Conference Information
Committee MVE  
Conference Date 2018-09-06 - 2018-09-07 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To MVE 
Conference Code 2018-09-MVE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Tag recommendation based on the relationship with user popularity on SNS 
Sub Title (in English)  
Keyword(1) Social network service  
Keyword(2) tag recommendation  
Keyword(3) graph model  
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1st Author's Name Xueting Wang  
1st Author's Affiliation The University of Tokyo (UTokyo)
2nd Author's Name Toshihiko Yamasaki  
2nd Author's Affiliation The University of Tokyo (UTokyo)
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Speaker Author-1 
Date Time 2018-09-06 15:15:00 
Presentation Time 25 minutes 
Registration for MVE 
Paper # MVE2018-17 
Volume (vol) vol.118 
Number (no) no.211 
Page pp.25-30 
#Pages 6 
Date of Issue 2018-08-30 (MVE) 

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