TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Practical Text Mining for Trend Analysis: Ontology to visualization in Aerospace Technology |
| 영문제목(English Title) |
Practical Text Mining for Trend Analysis: Ontology to visualization in Aerospace Technology |
| 저자(Author) |
Yoosin Kim
Yeonjin Ju
SeongGwan Hong
Seung Ryul Jeong
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| 원문수록처(Citation) |
VOL 11 NO. 08 PP. 4133 ~ 4145 (2017. 08) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Advances in science and technology are driving us to the better life but also forcing us to make more investment at the same time. Therefore, the government has provided the investment to carry on the promising futuristic technology successfully. Indeed, a lot of resources from the government have supported into the science and technology R&D projects for several decades. However, the performance of the public investments remains unclear in many ways, so thus it is required that planning and evaluation about the new investment should be on data driven decision with fact based evidence. In this regard, the government wanted to know the trend and issue of the science and technology with evidences, and has accumulated an amount of database about the science and technology such as research papers, patents, project reports, and R&D information. Nowadays, the database is supporting to various activities such as planning policy, budget allocation, and investment evaluation for the science and technology but the information quality is not reached to the expectation because of limitations of text mining to drill out the information from the unstructured data like the reports and papers. To solve the problem, this study proposes a practical text mining methodology for the science and technology trend analysis, in case of aerospace technology, and conduct text mining methods such as ontology development, topic analysis, network analysis and their visualization.
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| 키워드(Keyword) |
Text mining
Ontology
Trend Analysis
Aerospace Technology
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| 파일첨부 |
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