DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kim, Jihan | - |
dc.contributor.advisor | 김지한 | - |
dc.contributor.author | Kang, Yeonghun | - |
dc.date.accessioned | 2022-04-21T19:31:32Z | - |
dc.date.available | 2022-04-21T19:31:32Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=949004&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/295363 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 생명화학공학과, 2021.2,[iii, 30 p. :] | - |
dc.description.abstract | As big data becomes more important, automated research on information extraction using text mining is being actively conducted. In this study, we develop an algorithm that automatically extracts synthesis information from papers of metal organic framework using text mining. Use bag of words model to classify synthesis paragraphs of the paper. Using mechanical learning, recognize materials from synthesis paragraphs and extract the names of metal organic frameworks and precursors. Using natural language processing, we detect the extensive property and condition of the synthesis paragraph, and match with each material. The extracted materials are divided into metal precursors, organic precursors, and solvents to store synthesis information. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Metal organic framework▼aText mining▼aSynthesis▼aNatural language processing▼aMachine learning | - |
dc.subject | 금속 유기 구조체▼a텍스트마이닝▼a합성▼a자연어 처리▼a기계학습 | - |
dc.title | Development of text-mining toolkit for extracting metal organic framework synthesis method | - |
dc.title.alternative | 금속 유기 구조체 합성법 추출을 위한 텍스트마이닝 툴킷 개발 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :생명화학공학과, | - |
dc.contributor.alternativeauthor | 강영훈 | - |
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