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Paper Abstract and Keywords
Presentation 2016-02-22 14:45
A Note on Hierarchical Topic Detection from Heterogeneous Social Media Contents
Daichi Takehara, Ryosuke Harakawa, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we present a method of hierarchical topic detection from heterogeneous social media contents.
Our method firstly extracts latent features for comparing heterogeneous social media contents based on canonical correlation analysis.
Moreover, we construct a heterogeneous graph that has multiple types of nodes (i.e., heterogeneous social media contents), and hierarchically detect sets of contents with similar topics by analyzing community structure in the constructed heterogeneous graph.
As a result, hierarchical structure of the detected sets of contents is revealed.
Therefore, based on the revealed hierarchical structure, users can easily grasp overview of huge amount of heterogeneous social media contents and efficiently find the desired contents from them.
Experimental results on the real-world dataset that are collected from YouTube and Wikipedia show the effectiveness of our method.
Keyword (in Japanese) (See Japanese page) 
(in English) Social media / Hierarchical topic detection / Canonical correlation analysis / Graph Structure Analysis / YouTube video / Wikipedia article / /  
Reference Info. ITE Tech. Rep., vol. 40, no. 6, ME2016-54, pp. 193-196, Feb. 2016.
Paper # ME2016-54 
Date of Issue 2016-02-15 (MMS, CE, HI, ME, AIT) 
ISSN Print edition: ISSN 1342-6893    Online edition: ISSN 2424-1970
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Conference Information
Committee HI IEICE-IE AIT IEICE-ITS ME MMS CE  
Conference Date 2016-02-22 - 2016-02-23 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokudai 
Topics (in Japanese) (See Japanese page) 
Topics (in English) image processing etc 
Paper Information
Registration To ME 
Conference Code 2016-02-HI-IE-AIT-ITS-ME-MMS-CE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Note on Hierarchical Topic Detection from Heterogeneous Social Media Contents 
Sub Title (in English)  
Keyword(1) Social media  
Keyword(2) Hierarchical topic detection  
Keyword(3) Canonical correlation analysis  
Keyword(4) Graph Structure Analysis  
Keyword(5) YouTube video  
Keyword(6) Wikipedia article  
Keyword(7)  
Keyword(8)  
1st Author's Name Daichi Takehara  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Ryosuke Harakawa  
2nd Author's Affiliation Hokkaido University (Hokkaido Univ.)
3rd Author's Name Takahiro Ogawa  
3rd Author's Affiliation Hokkaido University (Hokkaido Univ.)
4th Author's Name Miki Haseyama  
4th Author's Affiliation Hokkaido University (Hokkaido Univ.)
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Speaker Author-1 
Date Time 2016-02-22 14:45:00 
Presentation Time 15 minutes 
Registration for ME 
Paper # MMS2016-21, CE2016-21, HI2016-21, ME2016-54, AIT2016-21 
Volume (vol) vol.40 
Number (no) no.6 
Page pp.193-196 
#Pages
Date of Issue 2016-02-15 (MMS, CE, HI, ME, AIT) 


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