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A metadata-based approach for research discipline prediction using machine learning techniques and distance metrics

<p>The dataset is based on&nbsp;the paper:&nbsp;</p> <p>Hoang-Son Pham, Hanne Poelmans&nbsp;and Amr Ali-Eldin &lsquo;&rsquo;A metadata-based approach for research discipline prediction using machine learning techniques and distance metrics&rsquo;&rsquo;, IEEE Access (2023).</p> <p>The dataset includes:&nbsp;</p> <p>1. a list of project metadata extracted from FRIS portal</p> <p>2. a list of VODS disciplines</p> <p>3. a distance matrix</p> <p>&nbsp;</p> <p>* Kindly refer to our paper for more details on the dataset.</p> <p>https://ieeexplore.ieee.org/document/10156853</p>

ShareScore

36/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
0

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