CFMf topic-model
Comparison with LDA and Top2Vec
Bibliographic Data
| ID | 21441874 |
|---|---|
| Authors | Jean-Charles Lamirel (0000-0001-7461-1785, Laboratoire Lorrain de Recherche en Informatique et ses Applications, corresponding author), Francis Lareau (0000-0002-0352-5246, Université du Québec à Montréal), Christophe Malaterre (0000-0003-1413-6710, Université du Québec à Montréal) |
| Year | 2024 |
| Volume | 129 |
| Issue | 10 |
| Pages | 6387-6405 |
| Publication date | 2024-10-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Scientometrics (JOURNAL) |
| Journal identifiers | ISSN: 0138-9130 • E-ISSN: 1588-2861 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s11192-024-05017-z |
| OpenAlex | W4396237870 |
| Language | EN |
| Citations received | 3 |
| References cited | 13 |
Data science · Information retrieval · Topic model · Computational and Text Analysis Methods · Computer Science · Scientific Computing and Data Management · Topic Modeling
Finding scientific topics
Density-Based Clustering Based on Hierarchical Density Estimates
Exploring the Space of Topic Coherence Measures
An overview of the history of Science of Science in China based on the use of bibliographic and citation data
Applications of Topic Models
The early days of contemporary philosophy of science
| Citations per year | 3 |
|---|---|
| Citation span | 2025 - 2025 (1) |
| Highly cited | No |