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The new public portal of CityUHK Scholars is now live and accessible to all users, marking a significant milestone in enhancing the visibility of our scholars' contributions and supporting the University's research strategies with cutting-edge technology. Among its many new features, the portal introduces fingerprints. 18 Jun 2025 [2 min read] |
What are Fingerprints?
Fingerprints are automatically generated key concepts derived from text data in Pure, the backend system of CityUHK Scholars. They create an index of weighted terms that provides a snapshot of the main topics covered in research outputs, researcher profiles, projects, and other records.
Using Natural Language Processing (NLP), the system scans text such as publication titles, abstracts, and descriptions, matching key concepts against scientific thesauri. It identifies relevant scientific areas and ranks concepts based on their frequency and location in the text, with higher weight given to concepts in titles. Multiple fingerprints can be aggregated by summing individual concept ranks and normalizing the results. The final fingerprints are displayed in CityUHK Scholars backend and portal as appropriate.
Which Content Type Generates Fingerprints?
Fingerprints are generated from various content types in Pure, and they update dynamically as new content is added:
Can I Manage Fingerprints?
Fingerprints are generated automatically using NLP, so manual addition or modification of fingerprints is not possible. However, you can influence which terms appear by including key concepts in your research interests within your researcher profile, as well as in the titles and abstracts/descriptions of your research works.
If you find the fingerprints irrelevant or not representative of your research, you can remove specific concepts or disable fingerprints entirely for your researcher profile or records. Below are the steps on how to do this for researcher profiles.
For more information, please refer to Elsevier's guide What does the Fingerprint Engine do?.
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