Name
Title | ||
|---|---|---|
Beyond MeSH: Fine-grained semantic indexing of biomedical literature based on weak supervision |
Abstract | ||
|---|---|---|
•Semantic indexing with MeSH descriptors may aggregate several distinct concepts.•Concept-occurrence is a good heuristic for fine-grained semantic indexing.•Models trained with concept-occurrence as weak supervision can achieve good accuracy.•Lexical and semantic features combined can lead to improved predictive performance.•Under-sampling the major class in training data, can also lead to further improvement. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.ipm.2020.102282 | Information Processing & Management |
Keywords | DocType | Volume |
Semantic indexing,MeSH,Biomedical literature,Weak supervision | Journal | 57 |
Issue | ISSN | Citations |
5 | 0306-4573 | 1 |
PageRank | References | Authors |
0.35 | 15 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anastasios Nentidis | 1 | 5 | 4.48 |
| Anastasia Krithara | 2 | 180 | 15.63 |
| Grigorios Tsoumakas | 3 | 2653 | 116.75 |
| Georgios Paliouras | 4 | 1510 | 120.93 |