Patent document clustering with deep embeddings
Bibliographic Data
| ID | 21442244 |
|---|---|
| Authors | Jaeyoung Kim (0000-0001-6983-7907, Gachon University), Janghyeok Yoon (0000-0002-8701-0695, Konkuk University), Eunjeong Park (0000-0002-8919-3165, Naver (South Korea), corresponding author), Eunjeong L Park (0000-0003-1117-894X), Sungchul Choi (0000-0002-5836-3838, Gachon University) |
| Year | 2020 |
| Volume | 123 |
| Issue | 2 |
| Pages | 563-577 |
| Publication date | 2020-05-01 |
| Peer Reviewed | Yes |
| 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/s11192-020-03396-7 |
| OpenAlex | W3013023945 |
| Language | EN |
| Citations received | 9 |
| References cited | 23 |
Cluster analysis · Data mining · Data science · Document clustering · Embedding · Feature (linguistics) · Field (mathematics) · Information retrieval · Machine learning · Process (computing) · Advanced Text Analysis Techniques · Artificial Intelligence · Biomedical Text Mining and Ontologies · Computer Science · Machine Learning in Materials Science
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The Research Trends of Text Classification Studies (2000-2020)
| Unique citing works | 9 |
|---|---|
| Citations per year | 2.25 |
| Citation span | 2022 - 2026 (5) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 7 |