| Paper Abstract and Keywords |
| Presentation |
2025-03-01 11:35
Extraction method of hierarchical organization name sequences for authors' affiliations using the Scopus API
-- Case of rule-based machine learning -- Takashi Ikegawa (Waseda University/The University of Tokyo) ET2024-67 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Recently, bibliometric analysis using a hierarchical organization name sequence (HONS),
which consists of institution, department, and section names, is employed for several research fields. In this paper, we propose the method to extract the HONSs for paper authors' affiliations from raw data obtained through Scopus application programming interface. To achieve this with high accuracy, we construct the HONS extraction rules consisting of 25 different patterns. Applying our scheme to papers published during 1990 - 2023 for the journal entitled ``IEEE Transactions on Information Theory'', we confirmed a matching rate of 94%. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
hierarchical organization name sequence / rule-based machine learning / bibliometric analysis / Scopus application programming interface / / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 124, no. 388, ET2024-67, pp. 26-33, March 2025. |
| Paper # |
ET2024-67 |
| Date of Issue |
2025-02-22 (ET) |
| 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 |
ET2024-67 |
| Conference Information |
| Committee |
ET |
| Conference Date |
2025-03-01 - 2025-03-01 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Shinshu University Faculty of Education |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Advanced Teaching and Learning Support Environment, etc. |
| Paper Information |
| Registration To |
ET |
| Conference Code |
2025-03-ET |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Extraction method of hierarchical organization name sequences for authors' affiliations using the Scopus API |
| Sub Title (in English) |
Case of rule-based machine learning |
| Keyword(1) |
hierarchical organization name sequence |
| Keyword(2) |
rule-based machine learning |
| Keyword(3) |
bibliometric analysis |
| Keyword(4) |
Scopus application programming interface |
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Takashi Ikegawa |
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Waseda University/The University of Tokyo (Waseda University/The University of Tokyo) |
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| Speaker |
Author-1 |
| Date Time |
2025-03-01 11:35:00 |
| Presentation Time |
25 minutes |
| Registration for |
ET |
| Paper # |
ET2024-67 |
| Volume (vol) |
vol.124 |
| Number (no) |
no.388 |
| Page |
pp.26-33 |
| #Pages |
8 |
| Date of Issue |
2025-02-22 (ET) |