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Title: NOUS: A Knowledge Graph Management System

Abstract

Knowledge graphs represent information as entities and relationships between them. For tasks such as natural language question answering or automated analysis of text, a knowledge graph provides valuable context to establish the specific type of entities being discussed. It allow us to derive better context about newly arriving information and leads to intelligent reasoning capabilities. We address two primary needs: A) Automated construction of knowledge graphs is a technically challenging, expensive process; and B) The ability to synthesize new information by monitoring newly emerging knowledge is a transformational capability that does not exist in state of the art systems.

Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
Contributing Org.:
Battelle Memorial Institute, Pacific Northwest Division (PNNL)
OSTI Identifier:
1366431
Report Number(s):
NOUS; 005341MLTPL00
Battelle IPID 30821-E
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Software
Software Revision:
00
Software Package Number:
005341
Software CPU:
MLTPL
Open Source:
Yes
MIT License.
Source Code Available:
Yes
Other Software Info:
Open Source available under MIT license.
Related Software:
The software is developed on top of the open source Apache Spark framework for large-scale, in-memory computing.
Country of Publication:
United States

Citation Formats

. NOUS: A Knowledge Graph Management System. Computer software. https://www.osti.gov//servlets/purl/1366431. Vers. 00. USDOE. 26 Jun. 2017. Web.
. (2017, June 26). NOUS: A Knowledge Graph Management System (Version 00) [Computer software]. https://www.osti.gov//servlets/purl/1366431.
. NOUS: A Knowledge Graph Management System. Computer software. Version 00. June 26, 2017. https://www.osti.gov//servlets/purl/1366431.
@misc{osti_1366431,
title = {NOUS: A Knowledge Graph Management System, Version 00},
author = {},
abstractNote = {Knowledge graphs represent information as entities and relationships between them. For tasks such as natural language question answering or automated analysis of text, a knowledge graph provides valuable context to establish the specific type of entities being discussed. It allow us to derive better context about newly arriving information and leads to intelligent reasoning capabilities. We address two primary needs: A) Automated construction of knowledge graphs is a technically challenging, expensive process; and B) The ability to synthesize new information by monitoring newly emerging knowledge is a transformational capability that does not exist in state of the art systems.},
url = {https://www.osti.gov//servlets/purl/1366431},
doi = {},
year = {Mon Jun 26 00:00:00 EDT 2017},
month = {Mon Jun 26 00:00:00 EDT 2017},
note =
}

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