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Paper Abstract and Keywords
Presentation 2021-03-05 10:15
A Proposal for Causal Inference with Subjective Evaluation
Daichi Ikeda, Hikaru Morita (Graduate School of Kanagawa Univ.) IT2020-146 ISEC2020-76 WBS2020-65
Abstract (in Japanese) (See Japanese page) 
(in English) Machine learning techniques such as deep learning are often used for identification and personal matching in information security.
In addition, an approach that increases the amount of data for training is generally used to improve the inference accuracy.
However, in cases where a large amount of data is not available, the accuracy cannot be improved.
In order to improve the inference accuracy, we propose a method to stimulate learning by adding subjective evaluation data without increasing the existing data.
Specifically, we add subjective evaluation data as new random variables to the existing random variables consisting of features, etc.
Here, for the interrelationship of the random variables, we took the approach of adding the random variables of subjective evaluation to the NBC (Naive Bayesian Classifier).
In addition, by taking the same approach as the Probabilistic Graphical Model (hereinafter referred to as PGM), the formulation is formulated as an extension of NBC, so to speak.
The validity of this method is evaluated as a problem of judging URL addresses for phishing and as a problem of judging conversational examples used in Telephone fraud.
Keyword (in Japanese) (See Japanese page) 
(in English) Naive Bayesian Classifier / Probablistic Graphical Model / d-separataion / / / / /  
Reference Info. IEICE Tech. Rep., vol. 120, no. 411, ISEC2020-76, pp. 208-212, March 2021.
Paper # ISEC2020-76 
Date of Issue 2021-02-25 (IT, ISEC, WBS) 
ISSN Online edition: ISSN 2432-6380
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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 IT2020-146 ISEC2020-76 WBS2020-65

Conference Information
Committee WBS IT ISEC  
Conference Date 2021-03-04 - 2021-03-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Joint Meeting of WBS, IT, and ISEC 
Paper Information
Registration To ISEC 
Conference Code 2021-03-WBS-IT-ISEC 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Proposal for Causal Inference with Subjective Evaluation 
Sub Title (in English)  
Keyword(1) Naive Bayesian Classifier  
Keyword(2) Probablistic Graphical Model  
Keyword(3) d-separataion  
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1st Author's Name Daichi Ikeda  
1st Author's Affiliation Graduate School of Kanagawa University (Graduate School of Kanagawa Univ.)
2nd Author's Name Hikaru Morita  
2nd Author's Affiliation Graduate School of Kanagawa University (Graduate School of Kanagawa Univ.)
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Speaker Author-1 
Date Time 2021-03-05 10:15:00 
Presentation Time 25 minutes 
Registration for ISEC 
Paper # IT2020-146, ISEC2020-76, WBS2020-65 
Volume (vol) vol.120 
Number (no) no.410(IT), no.411(ISEC), no.412(WBS) 
Page pp.208-212 
#Pages
Date of Issue 2021-02-25 (IT, ISEC, WBS) 


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