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Paper Abstract and Keywords
Presentation 2017-11-24 13:55
Comment Mining to Estimate Junior High-school Student Performance toward Improvement of Student Learning
Ichiro Niiya, Takayuki Nagai, Tsunenori Mine (Kyushu Univ) AI2017-12
Abstract (in Japanese) (See Japanese page) 
(in English) Estimating student performance is very useful for estimating students with poor grades early. In this research, we will estimate the performance from the retrospective sentences after the lesson described by junior high school students of the Learning Cram school and investigate the students' retrospect. In the estimation of the grades, each student made a backward sentence written after the lesson of the subject student himself / herself as a vector, followed by dimensional compression, and the student 's performance was estimated from various classifiers. In the survey of students' retrospective sentences, we examined words with high frequency of appearance by grades. As a result, the performance estimation accuracy using the binary weights and mutual information was better than the results of the previous research in the performance estimation. In the survey of retrospective sentences, it was found that the frequency of appearance and objects of respectful adverbs differed for the top grades and the students 'lower students' respect.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine learning, / Text mining / Junior high school student comments / performance estimation / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 326, AI2017-12, pp. 31-36, Nov. 2017.
Paper # AI2017-12 
Date of Issue 2017-11-17 (AI) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
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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 AI  
Conference Date 2017-11-24 - 2017-11-24 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To AI 
Conference Code 2017-11-AI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Comment Mining to Estimate Junior High-school Student Performance toward Improvement of Student Learning 
Sub Title (in English)  
Keyword(1) Machine learning,  
Keyword(2) Text mining  
Keyword(3) Junior high school student comments  
Keyword(4) performance estimation  
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1st Author's Name Ichiro Niiya  
1st Author's Affiliation Kyushu University (Kyushu Univ)
2nd Author's Name Takayuki Nagai  
2nd Author's Affiliation Kyushu University (Kyushu Univ)
3rd Author's Name Tsunenori Mine  
3rd Author's Affiliation Kyushu University (Kyushu Univ)
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Speaker Author-1 
Date Time 2017-11-24 13:55:00 
Presentation Time 25 minutes 
Registration for AI 
Paper # AI2017-12 
Volume (vol) vol.117 
Number (no) no.326 
Page pp.31-36 
#Pages
Date of Issue 2017-11-17 (AI) 


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