Science Citation Knowledge Extractor

SCKE is an open source tool that helps biomedical researchers understand how their work is being used by others, by analyzing the content in papers that cite them. This tool uses natural language processing and machine learning to extract the prominent themes and concepts discussed in the citing documents. By seeing what kinds of topics are discussed by citing articles, researchers can better understand how their work influences their peers and various disciplines in science. Additionally, SCKE allows biomedical researchers to explore other statistics about the publications that cite them, such as where citations are published (Journals), the distribution of keywords (Keywords), the similarity of papers to each other (Clustering), the similarity of papers to other famous works (TextCompare), and general statistics about the citations (Statistics). The data presented here are supplementary data required for anyone wishing to set up SCKE on their own system.

Data and Resources

Additional Info

Field Value
Author Lyons, Eric, Hahn-Powell, Gustave, Lent, Heather
Last Updated June 23, 2024, 17:21 (UTC)
Created June 23, 2024, 17:20 (UTC)
Citation Lyons, Eric, Hahn-Powell, Gustave, Lent, Heather 2017. Science Citation Knowledge Extractor. CyVerse Data Commons. DOI 10.7946/P29S5B
Date created in discovery environment 2017-10-23 17:34:20
Date last modified in discovery environment 2020-02-20 22:05:33
alternateIdentifier /b7946/p29s5b
identifierType DOI
is_deprecated false
publisher CyVerse Data Commons
resourceType data needed to run SCKE