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Paper Abstract and Keywords
Presentation 2024-04-11 15:30
[Invited Talk] Trust in the Recommender System and its Prediction based on the Performance Beliefs
Yoshinori Hijikata (KGU) NS2024-4
Abstract (in Japanese) (See Japanese page) 
(in English) This paper introduces our study on users’ perceived trust in the recommendation system. In recent years, as represented by the term “attention economy”, platformers have earned revenue by attracting users’ interest and attention to their services and contents, and by placing advertisements on them. Recommender systems have been introduced to encourage users to stay in a service or system for a long time. We have developed and validated a recommendation acceptance tendency scale that measures users’ deep trust in the recommender system. We have also analyzed the relationship between such deep trust and the user’s understanding of the performance of the recommender system (called ‘belief’ in psychology). This paper introduces the questions of the developed psychological scale, the method and results of its validation, and a prediction model of recommendation acceptance.
Keyword (in Japanese) (See Japanese page) 
(in English) Recommender system / Trust / Psychological Scale / Construct / Construct Validity / Trust Prediction Model / /  
Reference Info. IEICE Tech. Rep., vol. 124, no. 2, NS2024-4, pp. 17-22, April 2024.
Paper # NS2024-4 
Date of Issue 2024-04-04 (NS) 
ISSN 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)
Download PDF NS2024-4

Conference Information
Committee NS  
Conference Date 2024-04-11 - 2024-04-12 
Place (in Japanese) (See Japanese page) 
Place (in English) Okayama Prefectural Library + Online 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Communication traffic theory, Traffic and quality evaluation, Network performance evaluation, QoS/QoE, Reliability and robustness, Traffic and quality management, AI and machine learning, Network and system operation management, High capacity, low latency, many connections, General 
Paper Information
Registration To NS 
Conference Code 2024-04-NS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Trust in the Recommender System and its Prediction based on the Performance Beliefs 
Sub Title (in English)  
Keyword(1) Recommender system  
Keyword(2) Trust  
Keyword(3) Psychological Scale  
Keyword(4) Construct  
Keyword(5) Construct Validity  
Keyword(6) Trust Prediction Model  
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1st Author's Name Yoshinori Hijikata  
1st Author's Affiliation Kwansei Gakuin University (KGU)
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Speaker Author-1 
Date Time 2024-04-11 15:30:00 
Presentation Time 45 minutes 
Registration for NS 
Paper # NS2024-4 
Volume (vol) vol.124 
Number (no) no.2 
Page pp.17-22 
#Pages 6 
Date of Issue 2024-04-04 (NS) 

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