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HOLMES: A Hybrid Ontology-Learning Materials Engineering System

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개인저자Remolona, Miguel Francisco Miravite.
단체저자명Columbia University. Chemical Engineering.
서명/저자사항HOLMES: A Hybrid Ontology-Learning Materials Engineering System.
발행사항[S.l.] : Columbia University., 2018
발행사항Ann Arbor : ProQuest Dissertations & Theses, 2018
형태사항194 p.
소장본 주기School code: 0054.
ISBN9780438277939
일반주기 Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
Adviser: Venkat Venkatasubramanian.
요약Designing and discovering novel materials is challenging problem in many domains such as fuel additives, composites, pharmaceuticals, and so on. At the core of all this are models that capture how the different domain-specific data, information,
요약The HOLMES framework starts with journal articles that are in the Portable Document Format (PDF) and ends with the assignment of the entries in the journal articles into ontologies. While this might seem to be a simple task of information extrac
요약In the development of the information extraction tasks, we note that there are new problems that have not arisen in previous information extraction work in the literature. The first is the necessity to extract auxiliary information in the form o
요약In this work, the HOLMES framework is presented as a whole, describing our successful progress as well as unsolved problems, which might help future research on this topic. The ontology is then presented to help in the identification of the rele
일반주제명Chemical engineering.
Computer science.
언어영어
기본자료 저록Dissertation Abstracts International79-12B(E).
Dissertation Abstract International
대출바로가기http://www.riss.kr/pdu/ddodLink.do?id=T14999830

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