Work

Clustering Narrow-Domain Scientific Text Using Unsupervised and Similarity-Based Approaches

Year: 2025

Type: article

Abstract: 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

Source: International Journal of Technology

DOI: 10.14716/ijtech.v16i5.7110

Authors: Saiful Akbar, Anindya Prameswari Ekaputri, William Fu, Rahmah Khoirussyifa’ Nurdini, Salman Ma’arif Achsien, Benhard Sitohang

Language: English

Topic: Advanced Clustering Algorithms Research

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $1,000

Funder: Rijksuniversiteit Groningen

OpenAlex ID: W4414393294