arXiv
Open Access
2025
Experimental Evaluation of Dynamic Topic Modeling Algorithms
Ngozichukwuka Onah
Nadine Steinmetz
Hani Al-Sayeh
Kai-Uwe Sattler
Abstrak
The amount of text generated daily on social media is gigantic and analyzing this text is useful for many purposes. To understand what lies beneath a huge amount of text, we need dependable and effective computing techniques from self-powered topic models. Nevertheless, there are currently relatively few thorough quantitative comparisons between these models. In this study, we compare these models and propose an assessment metric that documents how the topics change in time.
Topik & Kata Kunci
Penulis (4)
N
Ngozichukwuka Onah
N
Nadine Steinmetz
H
Hani Al-Sayeh
K
Kai-Uwe Sattler
Akses Cepat
Informasi Jurnal
- Tahun Terbit
- 2025
- Bahasa
- en
- Sumber Database
- arXiv
- Akses
- Open Access ✓