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Elsevier Fingerprint Engine mines the text of scientific documents – publication abstracts, funding announcements, project summaries, patents, proposals– to create an index of weighted terms which defines the text Fingerprint visualization.
By aggregating and comparing Fingerprint indices, the Elsevier Fingerprint Engine enables institutions to look beyond metadata and expose valuable connections among people, publications, funding opportunities and ideas. The Elsevier Fingerprint Engine powers many solutions including Pure, comprehensive information management system, and Expert Lookup, an Elsevier tool for finding reviewers.
Covering a wide range of subject areas with a collection of thesauri, the Elsevier Fingerprint Engine uses a variety of thesauri to support applications pertaining to different subject areas. By applying a wide range of thesauri, Elsevier can develop solutions for researchers in but not limited to: the life sciences, engineering, earth and environmental sciences, arts and humanities, social sciences, mathematics and agriculture.
The Elsevier Fingerprint Engine creates Fingerprint indices:
The Elsevier Fingerprint Engine applies a variety of Natural Language Processing (NLP) techniques to mine the text of scientific documents, including publication abstracts, funding announcements and awards, project summaries, patents, proposals, applications and other sources.
Key concepts that define the text are identified in thesauri spanning all the major disciplines.
The Elsevier Fingerprint Engine creates an index of weighted terms that defines the text, known as a Fingerprint index.
By aggregating and comparing Fingerprint indices of people, publications, funding opportunities and ideas, the Elsevier Fingerprint Engine reveals insightful connections with practical applications. These products use Fingerprint indices:
Pure creates Fingerprint indices for your researchers’ expertise, matching the Fingerprint indices of funding opportunities to your researchers
