풍력에너지 저널 (Journal of Wind Energy)

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Info. Vol.11 - No.2 (2020.06.30)
DOI kwea.2020.11.2.004
Title 풍력에너지저널 문헌검토에 의한 주제모델링 (Topic Modeling with a Literature Review of the Journal of Wind Energy
Authors 김현구*․유기완**․백인수***
Institutions * 한국에너지기술연구원 신재생자원지도연구실 (교신저자) ** 전북대학교 항공우주공학과 교수 *** 강원대학교 기계의용·메카트로닉스·재료공학부 교수
Abstract In celebration of the 10th anniversary of the publication of the Journal of Wind Energy, we intend to grasp research trends through a literature review of the journal’s papers and seek ways to improve the quality of the journal. The text mining technique was used to extract a document-term matrix, and topic modeling was performed using latent semantic analysis and fuzzy K-means clustering. From the comparison of the topic modeling results with manual categorization by experts, it is anticipated that supervised learning is recommended by including the specific topic classification by author in the bibliography metadata for meaningful topic modeling in the future. We confirmed that it is necessary to apply different weights because the descriptive level of title, keyword, and abstract are different when specifying the topic of the research paper. The characteristic theme of the Journal of Wind Energy was identified as “offshore wind,” and research institutes and universities are participating widely, but it is of concern because the participation of industry is declining.
Keyword Wind energy (풍력에너지), Literature survey (문헌검토), Text mining (텍스트마이닝), Topic modeling (주제모델링), Document-term matrix (문서-단어행렬), Latent Semantic Analysis (LSA, 잠재의미분석)
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