Abstract
This paper describes the Antinomyra System that participated in the BioASQ Task 2a Challenge for the large-scale biomedical semantic indexing. The system can automatically annotate MeSH terms for MEDLINE citations using only title and abstract information. With respect to the official test set (batch 3, week 5), based on 1867 annotated citations out of all 4533 citations (June 6, 2014), our best submission achieved 0.6199 in flat Micro F-measure. This is 9.8% higher than the performance of official NLM solution Medical Text Indexer (MTI), which achieved 0.5647 in flat F-measure.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1311-1318 |
| Number of pages | 8 |
| Journal | CEUR Workshop Proceedings |
| Volume | 1180 |
| State | Published - 2014 |
| Event | 2014 Cross Language Evaluation Forum Conference, CLEF 2014 - Sheffield, United Kingdom Duration: Sep 15 2014 → Sep 18 2014 |
Keywords
- Learning to rank
- Logistic regression
- MeSH indexing
- Multi-label classification
ASJC Scopus subject areas
- General Computer Science