About: Exploration and Discovery of the COVID-19 Literature through Semantic Visualization

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Exploration and Discovery of the COVID-19 Literature through Semantic Visualization Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Exploration and Discovery of the COVID-19 Literature through Semantic Visualization
Creator	Pustejovsky, James Cochran, Brent Tu, Jingxuan Verhagen, Marc
source	ArXiv
abstract	We are developing semantic visualization techniques in order to enhance exploration and enable discovery over large datasets of complex networks of relations. Semantic visualization is a method of enabling exploration and discovery over large datasets of complex networks by exploiting the semantics of the relations in them. This involves (i) NLP to extract named entities, relations and knowledge graphs from the original data; (ii) indexing the output and creating representations for all relevant entities and relations that can be visualized in many different ways, e.g., as tag clouds, heat maps, graphs, etc.; (iii) applying parameter reduction operations to the extracted relations, creating%22relation containers%22, or functional entities that can also be visualized using the same methods, allowing the visualization of multiple relations, partial pathways, and exploration across multiple dimensions. Our hope is that this will enable the discovery of novel inferences over relations in complex data that otherwise would go unnoticed. We have applied this to analysis of the recently released CORD-19 dataset.
has issue date	2020-07-03(xsd:dateTime)
has license	arxiv
sha1sum (hex)	ffaaab9163e6d9fccd83bb596f643824ce9c043f
resource representing a document's title	Exploration and Discovery of the COVID-19 Literature through Semantic Visualization
resource representing a document's body	covid:ffaaab9163e6d9fccd83bb596f643824ce9c043f#body_text
is schema:about of	named entity 'relation' named entity 'CORD' named entity 'ALLOWING' named entity 'semantics' named entity 'order' »more»

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software