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Paper Abstract and Keywords
Presentation 2024-01-24 09:10
Datetime Feature Recommendation System by Using Data Column Names
Satoshi Masuda, Tomohiro Takeda (TCU) KBSE2023-58
Abstract (in Japanese) (See Japanese page) 
(in English) Analysis to gain new knowledge from huge amounts of data is called data science, and its widespread use is now socially important. Feature engineering, the process of extracting features from data, is one of the main tasks in data science, and since this task relies on the experience of experts, research is being conducted to automate it. In our wok, we propose a novel approach to automate feature identification from textual information in data column names. Specifically, we use techniques of natural language processing and source code analysis, for data descriptions and source codes in Python notebooks to create a knowledge database with a particular focus on datetime features. We develop a recommendation system of datetime features for newly given text information based on that knowledge database. Based on our previous work, this paper reports a case study in which word vectorization was changed from the conventional one-hot vector to word embedding. In experiments, we confirmed the classification accuracy of the knowledge database, applied the database to actual forecasting tasks such as home price forecasting, and confirmed for accuracy gain.
Keyword (in Japanese) (See Japanese page) 
(in English) data science / automatic feature engineering / natural language processing / datetime API / / / /  
Reference Info. IEICE Tech. Rep., vol. 123, no. 352, KBSE2023-58, pp. 43-48, Jan. 2024.
Paper # KBSE2023-58 
Date of Issue 2024-01-16 (KBSE) 
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 KBSE2023-58

Conference Information
Committee KBSE  
Conference Date 2024-01-23 - 2024-01-24 
Place (in Japanese) (See Japanese page) 
Place (in English)  
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To KBSE 
Conference Code 2024-01-KBSE 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Datetime Feature Recommendation System by Using Data Column Names 
Sub Title (in English)  
Keyword(1) data science  
Keyword(2) automatic feature engineering  
Keyword(3) natural language processing  
Keyword(4) datetime API  
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1st Author's Name Satoshi Masuda  
1st Author's Affiliation Tokyo City University (TCU)
2nd Author's Name Tomohiro Takeda  
2nd Author's Affiliation Tokyo City University (TCU)
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Speaker Author-1 
Date Time 2024-01-24 09:10:00 
Presentation Time 45 minutes 
Registration for KBSE 
Paper # KBSE2023-58 
Volume (vol) vol.123 
Number (no) no.352 
Page pp.43-48 
#Pages 6 
Date of Issue 2024-01-16 (KBSE) 

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