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Paper Abstract and Keywords
Presentation 2022-02-21 17:00
A Note on Interest level Estimation Using Users' Behavior Information -- Validating the Effectiveness of Feature Integration with Multiple Users --
Kyohei Kamikawa, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama (Hokkaido Univ.)
Abstract (in Japanese) (See Japanese page) 
(in English) In this paper, we verify the effectiveness of feature integration with multi-user behavior information for interest level estimation in contents. Users' behavior information during viewing contents is correlated with the users' preferences for the contents, and is effective for interest level estimation. Furthermore, since behavior information of the target user, which is the target of interest level estimation, is correlated with behavior information of other users, the accuracy of interest level estimation is expected to be improved by simultaneously using the behavior information of target user and other users. Therefore, in this paper, we focus on semi-supervised ordinally multi-modal Gaussian process latent variable model (semi-OMGP), which is one of the methods that can use behavior information of multiple users. semi-OMGP integrates features calculated from content and multi-user behavior information, and we verify the accuracy of interest level estimation based on the integrated features to confirm the effectiveness of using multi-user behavior information.
Keyword (in Japanese) (See Japanese page) 
(in English) Feature integration / Gaussian process / Multiple user / Behavior feature / Interest level estimation / / /  
Reference Info. ITE Tech. Rep., vol. 46, no. 6, ME2022-45, pp. 103-107, Feb. 2022.
Paper # ME2022-45 
Date of Issue 2022-02-14 (MMS, ME, AIT) 
ISSN Print edition: ISSN 1342-6893    Online edition: ISSN 2424-1970
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Conference Information
Committee AIT ME MMS IEICE-IE IEICE-ITS  
Conference Date 2022-02-21 - 2022-02-22 
Place (in Japanese) (See Japanese page) 
Place (in English) online 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To ME 
Conference Code 2022-02-AIT-ME-MMS-IE-ITS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Note on Interest level Estimation Using Users' Behavior Information 
Sub Title (in English) Validating the Effectiveness of Feature Integration with Multiple Users 
Keyword(1) Feature integration  
Keyword(2) Gaussian process  
Keyword(3) Multiple user  
Keyword(4) Behavior feature  
Keyword(5) Interest level estimation  
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1st Author's Name Kyohei Kamikawa  
1st Author's Affiliation Hokkaido University (Hokkaido Univ.)
2nd Author's Name Keisuke Maeda  
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 2022-02-21 17:00:00 
Presentation Time 15 minutes 
Registration for ME 
Paper # MMS2022-20, ME2022-45, AIT2022-20 
Volume (vol) vol.46 
Number (no) no.6 
Page pp.103-107 
#Pages
Date of Issue 2022-02-14 (MMS, ME, AIT) 


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