Abstract
Using Natural Language Process (NLP) as an efficient way to research paper is important when user feedback is sparse or unavailable. The task of text mining research paper is challenging, mainly due to the problem of unique characteristics such as jargon. Nowadays, there exist many language models that learn deep semantic representations by being trained on huge corpora. In this paper, we specify the NLP pre-processing process with Economics journal paper and apply it to a deep learning model to extract keywords. Here, we focus on the strength of NLP when applied to an unknown field. The analysis result shows the possibility and potential usefulness of the relationship research between keywords in research papers.
Original language | English |
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Title of host publication | ICUFN 2021 - 2021 12th International Conference on Ubiquitous and Future Networks |
Publisher | IEEE Computer Society |
Pages | 75-77 |
Number of pages | 3 |
ISBN (Electronic) | 9781728164762 |
DOIs | |
Publication status | Published - 2021 Aug 17 |
Event | 12th International Conference on Ubiquitous and Future Networks, ICUFN 2021 - Virtual, Jeju Island, Korea, Republic of Duration: 2021 Aug 17 → 2021 Aug 20 |
Publication series
Name | International Conference on Ubiquitous and Future Networks, ICUFN |
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Volume | 2021-August |
ISSN (Print) | 2165-8528 |
ISSN (Electronic) | 2165-8536 |
Conference
Conference | 12th International Conference on Ubiquitous and Future Networks, ICUFN 2021 |
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Country/Territory | Korea, Republic of |
City | Virtual, Jeju Island |
Period | 21/8/17 → 21/8/20 |
Bibliographical note
Funding Information:This work was supported by the National Research Foundation of Korea grant (NRF-2019R1A2C1084778). Correspondence should be addressed to jseok14@korea.ac.kr
Publisher Copyright:
© 2021 IEEE.
Keywords
- BERT
- Economics Journal Paper
- Natural Language Processing
- Preprocessing
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Hardware and Architecture