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Building Scalable Knowledge Graphs for Earth Science
NTRS Full-Text: Click to View  [PDF Size: 1.5 MB]
Author and Affiliation:
Ramachandran, Rahul(NASA Marshall Space Flight Center, Huntsville, AL, United States)
Maskey, Manil(NASA Marshall Space Flight Center, Huntsville, AL, United States)
Gatlin, Patrick(NASA Marshall Space Flight Center, Huntsville, AL, United States)
Zhang, Jia(Carnegie-Mellon Univ., Pittsburgh, PA, United States)
Duan, Xiaoyi(Carnegie-Mellon Univ., Pittsburgh, PA, United States)
Miller, J. J.(Alabama Univ., Huntsville, AL, United States)
Bugbee, Kaylin(Alabama Univ., Huntsville, AL, United States)
Christopher, Sundar(Alabama Univ., Huntsville, AL, United States)
Freitag, Brian(Alabama Univ., Huntsville, AL, United States)
Abstract: Knowledge Graphs link key entities in a specific domain with other entities via relationships. From these relationships, researchers can query knowledge graphs for probabilistic recommendations to infer new knowledge. Scientific papers are an untapped resource which knowledge graphs could leverage to accelerate research discovery. Goal: Develop an end-to-end (semi) automated methodology for constructing Knowledge Graphs for Earth Science.
Publication Date: Dec 11, 2017
Document ID:
20170011712
(Acquired Dec 21, 2017)
Subject Category: DOCUMENTATION AND INFORMATION SCIENCE; GEOSCIENCES (GENERAL)
Report/Patent Number: MSFC-E-DAA-TN50133
Document Type: Oral/Visual Presentation
Meeting Information: AGU Fall Meeting 2017; 11-15 Dec. 2017; New Orleans, LA; United States
Meeting Sponsor: American Geophysical Union; Washington, DC, United States
Contract/Grant/Task Num: NNM11AA01A
Financial Sponsor: NASA Marshall Space Flight Center; Huntsville, AL, United States
Organization Source: NASA Marshall Space Flight Center; Huntsville, AL, United States
Description: 1p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright; Portions of the document may include copyright protected material
NASA Terms: KNOWLEDGE BASES (ARTIFICIAL INTELLIGENCE); KNOWLEDGE BASED SYSTEMS; INFORMATION ANALYSIS; ALGORITHMS; SEMANTICS; TAXONOMY; MACHINE LEARNING; GRAPHS (CHARTS); HEURISTIC METHODS; EARTH SCIENCES; RESEARCH MANAGEMENT; DOCUMENTS; METADATA
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