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Paper Abstract and Keywords
Presentation 2019-02-22 15:10
Active Inference of Variable Labels Using Annotation to Some Variable Labels in Data Jackets
Hiroo Iwanaga (UTokyo/NTT DATA MSI), Teruaki Hayashi, Yukio Ohsawa (UTokyo) AI2018-44
Abstract (in Japanese) (See Japanese page) 
(in English) Data Jacket (DJ) is a framework for sharing summaries of the data and encouraging collaboration and utilization of data in the market, with the data itself hidden. Variable labels (VLs) are described in DJs as the name or meaning of variables in the data. While VLs are the key information for planning data utilization or data collection, DJs have missing VLs because the registration rule of DJs does not force data holders to enter all the information about variables in the data. To infer likely VLs in DJs which are not explicitly in the outline of data, matrix-based method (MBM) are proposed. However, MBM is difficult for DJ users to reflect their prior knowledge or requirement about variables of the data (e.g. “some VLs should be included in the DJ”). In this paper, we propose a method for inferring VLs using ODs and annotation to some VLs, extending MBM to be applicable for active learning situations. Our method enables DJ users to update the inference results as needed by adding the annotation to VLs.
Keyword (in Japanese) (See Japanese page) 
(in English) Data Jacket / Variable Label / active learning / partial annotation / / / /  
Reference Info. IEICE Tech. Rep., vol. 118, no. 453, AI2018-44, pp. 39-44, Feb. 2019.
Paper # AI2018-44 
Date of Issue 2019-02-15 (AI) 
ISSN Online edition: ISSN 2432-6380
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 2019-02-22 - 2019-02-23 
Place (in Japanese) (See Japanese page) 
Place (in English)  
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Paper Information
Registration To AI 
Conference Code 2019-02-AI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Active Inference of Variable Labels Using Annotation to Some Variable Labels in Data Jackets 
Sub Title (in English)  
Keyword(1) Data Jacket  
Keyword(2) Variable Label  
Keyword(3) active learning  
Keyword(4) partial annotation  
1st Author's Name Hiroo Iwanaga  
1st Author's Affiliation The University of Tokyo/NTT DATA Mathematical Systems Inc. (UTokyo/NTT DATA MSI)
2nd Author's Name Teruaki Hayashi  
2nd Author's Affiliation The University of Tokyo (UTokyo)
3rd Author's Name Yukio Ohsawa  
3rd Author's Affiliation The University of Tokyo (UTokyo)
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Speaker Author-1 
Date Time 2019-02-22 15:10:00 
Presentation Time 20 minutes 
Registration for AI 
Paper # AI2018-44 
Volume (vol) vol.118 
Number (no) no.453 
Page pp.39-44 
Date of Issue 2019-02-15 (AI) 

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