Abstract
The 2014 BioASQ challenge 2a tasks participants with assigning semantic tags to biomedical journal abstracts. We present a system that uses Latent Semantic Analysis to identify semantically similar documents in MEDLINE to an unlabeled abstract, and then uses a novel ranking scheme to select a list of MeSH headers from candidates drawn from the most similar documents. Our approach achieved good precision, but suffered in terms of recall. We describe several possible strategies to improve our system's performance.
| Original language | English (US) |
|---|---|
| Title of host publication | CLEF 2014 - Working Notes for CLEF 2014 Conference |
| Publisher | CEUR-WS |
| Pages | 1275-1282 |
| Number of pages | 8 |
| Volume | 1180 |
| State | Published - 2014 |
| Event | 2014 Cross Language Evaluation Forum Conference, CLEF 2014 - Sheffield, United Kingdom Duration: Sep 15 2014 → Sep 18 2014 |
Other
| Other | 2014 Cross Language Evaluation Forum Conference, CLEF 2014 |
|---|---|
| Country/Territory | United Kingdom |
| City | Sheffield |
| Period | 9/15/14 → 9/18/14 |
ASJC Scopus subject areas
- General Computer Science