Name
Abstract | ||
|---|---|---|
Motivation: Chemical named entity recognition is used to automatically identify mentions to chemical compounds in text and is the basis for more elaborate information extraction. However, only a small number of applications are freely available to identify such mentions. Particularly challenging and useful is the identification of International Union of Pure and Applied Chemistry (IUPAC) chemical compounds, which due to the complex morphology of IUPAC names requires more advanced techniques than that of brand names. Results: We present CheNER, a tool for automated identification of systematic IUPAC chemical mentions. We evaluated different systems using an established literature corpus to show that CheNER has a superior performance in identifying IUPAC names specifically, and that it makes better use of computational resources. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1093/bioinformatics/btt639 | BIOINFORMATICS |
Field | DocType | Volume |
Data mining,Information retrieval,Computer science,Chemical nomenclature,Named entity,Information extraction,Software,Artificial intelligence,Natural language processing,Named-entity recognition | Journal | 30 |
Issue | ISSN | Citations |
7 | 1367-4803 | 10 |
PageRank | References | Authors |
0.73 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anabel Usié | 1 | 100 | 3.88 |
| Rui Alves | 2 | 196 | 32.99 |
| Francesc Solsona | 3 | 225 | 27.39 |
| Miguel Vazquez | 4 | 49 | 3.98 |
| Alfonso Valencia | 5 | 2577 | 322.43 |