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Paper Abstract and Keywords
Presentation 2023-03-14 16:55
Automatic Dataset Collection and Formatting Techniques for Machine Learning Systems
Takako Kawaguchi, Toshiyuki Kurabayashi, Haruto Tanno (former NTT) SS2022-57
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, as machine learning models have become larger and larger, the scale of data required for training has also been increasing. For this reason, more and more users are collecting training data from the abundant information resources on the web. However, web pages have a variety of screen configurations, and the location of data varies greatly depending on the configuration. Therefore, when extracting similar information from multiple Web pages with different screen configurations at once, it is necessary to set the extraction location for each screen configuration and provide examples. In this paper, we propose a technique that can extract similar data regardless of the differences in screen configurations of web pages. The proposed model allows users to retrieve desired data from multiple web pages with different screen configurations by simply indicating the data to be extracted and few examples of web pages on which the data resides. This is because the model takes into account the similarity of the text strings of data extracted in the input-output examples and the partial locations where the data exists, thereby limiting the impact of differences in the screen configuration of the entire Web page. In addition, we conducted evaluation experiments on the proposed model and showed that it can extract targets from multiple web pages with different screen configurations from the example web page.
Keyword (in Japanese) (See Japanese page) 
(in English) Machine Learning Engineering / Machine Learning / Web Scraping / Crawling / Data Collection / Regular Expressions / Data Extraction / Information Extraction  
Reference Info. IEICE Tech. Rep., vol. 122, no. 432, SS2022-57, pp. 61-66, March 2023.
Paper # SS2022-57 
Date of Issue 2023-03-07 (SS) 
ISSN 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 SS  
Conference Date 2023-03-14 - 2023-03-15 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To SS 
Conference Code 2023-03-SS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Automatic Dataset Collection and Formatting Techniques for Machine Learning Systems 
Sub Title (in English)  
Keyword(1) Machine Learning Engineering  
Keyword(2) Machine Learning  
Keyword(3) Web Scraping  
Keyword(4) Crawling  
Keyword(5) Data Collection  
Keyword(6) Regular Expressions  
Keyword(7) Data Extraction  
Keyword(8) Information Extraction  
1st Author's Name Takako Kawaguchi  
1st Author's Affiliation Nippon Telegraph and Telephone Corporation (former NTT)
2nd Author's Name Toshiyuki Kurabayashi  
2nd Author's Affiliation Nippon Telegraph and Telephone Corporation (former NTT)
3rd Author's Name Haruto Tanno  
3rd Author's Affiliation Nippon Telegraph and Telephone Corporation (former NTT)
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Speaker Author-1 
Date Time 2023-03-14 16:55:00 
Presentation Time 25 minutes 
Registration for SS 
Paper # SS2022-57 
Volume (vol) vol.122 
Number (no) no.432 
Page pp.61-66 
#Pages
Date of Issue 2023-03-07 (SS) 


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