Clustering Narrow-Domain Scientific Text Using Unsupervised and Similarity-Based Approaches
Clustering scientific papers published by authors is useful for discovering fellow authors with similar interests or research groups in the institution. In this study, we explore the use of scientific text clustering with an unsupervised approach to
Authors
- Saiful Akbar (ORCID: https://orcid.org/0000-0001-9314-5310)
- Anindya Prameswari Ekaputri (ORCID: https://orcid.org/0009-0007-8736-7612)
- William Fu (ORCID: https://orcid.org/0009-0002-5328-293X)
- Rahmah Khoirussyifa’ Nurdini
- Benhard Sitohang
- Salman Ma’arif Achsien
Publication Details
- Journal
- International Journal of Technology
- Published
- 2025-09-22
- DOI
- https://doi.org/10.14716/ijtech.v16i5.7110
- Primary Topic
- Advanced Text Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Rijksuniversiteit Groningen