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Paper Abstract and Keywords
Presentation 2011-12-16 16:50
A Transition Probability Model for Detecting both Information and Users
Satoshi Aoki, Jianwei Zhang, Yukiko Kawai, Yoshinori Kubota, Takuya Osaki, Toyokazu Akiyama (Kyoto Sangyo Univ) DE2011-49
Abstract (in Japanese) (See Japanese page) 
(in English) PageRank algorithm can achieve a ranking result of a large amount of pages by forming a transition probability matrix consisting of the hyperlinks between pages. However, as for the increasing CGM contents, for example, Blog and Twitter, links are structured by not only between contents and contents, but also between contents and users. Consequently, the conventional ranking model that only analyzes links between pages is difficult to rank pages and users all together at once. We propose a real-time ranking model of simultaneously pages and users, and forming a transition probability matrix consisting of both pages and users by analyzing relationship between pages and users. In this paper, first, we describe the constructing method of a graph based on the relationship of page-page, page-user and user-user, and then we explain the forming method the construction of its corresponding matrix and the ranking calculation method. Finally, we evaluate proposed model by our developed system from experiment.
Keyword (in Japanese) (See Japanese page) 
(in English) Information retrieval / User search / Transition probability matrix / Social services / / / /  
Reference Info. IEICE Tech. Rep., vol. 111, no. 361, DE2011-49, pp. 53-58, Dec. 2011.
Paper # DE2011-49 
Date of Issue 2011-12-09 (DE) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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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Conference Information
Committee DE  
Conference Date 2011-12-16 - 2011-12-16 
Place (in Japanese) (See Japanese page) 
Place (in English) Kyoto Sangyo University 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To DE 
Conference Code 2011-12-DE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Transition Probability Model for Detecting both Information and Users 
Sub Title (in English)  
Keyword(1) Information retrieval  
Keyword(2) User search  
Keyword(3) Transition probability matrix  
Keyword(4) Social services  
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1st Author's Name Satoshi Aoki  
1st Author's Affiliation Kyoto Sangyo University (Kyoto Sangyo Univ)
2nd Author's Name Jianwei Zhang  
2nd Author's Affiliation Kyoto Sangyo University (Kyoto Sangyo Univ)
3rd Author's Name Yukiko Kawai  
3rd Author's Affiliation Kyoto Sangyo University (Kyoto Sangyo Univ)
4th Author's Name Yoshinori Kubota  
4th Author's Affiliation Kyoto Sangyo University (Kyoto Sangyo Univ)
5th Author's Name Takuya Osaki  
5th Author's Affiliation Kyoto Sangyo University (Kyoto Sangyo Univ)
6th Author's Name Toyokazu Akiyama  
6th Author's Affiliation Kyoto Sangyo University (Kyoto Sangyo Univ)
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Speaker Author-1 
Date Time 2011-12-16 16:50:00 
Presentation Time 25 minutes 
Registration for DE 
Paper # DE2011-49 
Volume (vol) vol.111 
Number (no) no.361 
Page pp.53-58 
#Pages
Date of Issue 2011-12-09 (DE) 


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