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Paper Abstract and Keywords
Presentation 2018-06-08 11:30
Web video search reranking via graph-based soft clustering using heterogeneous metadata integration
Soh Yoshida, Mitsuji Muneyasu (Kansai Univ.) SIS2018-8
Abstract (in Japanese) (See Japanese page) 
(in English) This paper addresses the problem of analyzing a heterogeneous graph for extracting topics including videos in a dataset and improving the performance of video retrieval. Unlike previous works which only focus on an individual video graph, the proposed method leverages the ``mutual reinforcement'' of heterogeneous objects such as videos, their associated tags, and users obtained by social influence mining. In order to represent multiple types of relationships between them, the proposed method attempts to extract latent features which mean topics on a target dataset from a video group obtained by a keyword search using a heterogeneous graph-based soft clustering approach. Specifically, the proposed method constructs three subgraphs: a user-tag graph, a video-video graph, and a video-tag graph. We combine the three types of graphs to obtain the heterogeneous graph. Then the extraction of latent features becomes feasible by applying graph-based soft clustering to the heterogeneous graph and grouping different types of data as clusters. By estimating the membership of each cluster for each video, the proposed method defines a video similarity measure and formulates the video search reranking as an optimization problem.
Keyword (in Japanese) (See Japanese page) 
(in English) video retrieval / reranking / metadata / graph-based soft clustering / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 73, SIS2018-8, pp. 69-74, June 2018.
Paper # SIS2018-8 
Date of Issue 2018-05-31 (SIS) 
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)
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Conference Information
Committee SIS IPSJ-AVM ITE-3DMT  
Conference Date 2018-06-07 - 2018-06-08 
Place (in Japanese) (See Japanese page) 
Place (in English) Jozankei View Hotel 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Intelligent Multimedia Systems, Applied Enbedded Systems, Three-Dimensional Image Technology (3DIT), etc. 
Paper Information
Registration To SIS 
Conference Code 2018-06-SIS-AVM-3DIT 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Web video search reranking via graph-based soft clustering using heterogeneous metadata integration 
Sub Title (in English)  
Keyword(1) video retrieval  
Keyword(2) reranking  
Keyword(3) metadata  
Keyword(4) graph-based soft clustering  
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1st Author's Name Soh Yoshida  
1st Author's Affiliation Kansai University (Kansai Univ.)
2nd Author's Name Mitsuji Muneyasu  
2nd Author's Affiliation Kansai University (Kansai Univ.)
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Speaker Author-1 
Date Time 2018-06-08 11:30:00 
Presentation Time 20 minutes 
Registration for SIS 
Paper # SIS2018-8 
Volume (vol) vol.118 
Number (no) no.73 
Page pp.69-74 
#Pages 6 
Date of Issue 2018-05-31 (SIS) 

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